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Add probabilistic stimulus selection task entries
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‎public/psyflow-web/task-manifest.json‎

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"download_url": "https://github.com/TaskBeacon/H000038-two-armed-bandit/archive/refs/heads/main.zip",
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"run_url": "https://taskbeacon.github.io/psyflow-web/?task=H000038-two-armed-bandit",
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"last_updated": "2026-04-03T15:06:58Z"
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},
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{
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"directory": "H000040-probabilistic-stimulus-selection",
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"id": "H000040",
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"slug": "probabilistic-stimulus-selection",
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"title": "Probabilistic Stimulus Selection Task",
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"acquisition": "behavior",
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"maturity": "prototype",
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"release_tag": "v0.1.0-dev",
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"short_description": "Browser preview of the kana-based probabilistic stimulus selection task with learning and transfer phases",
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"repo_url": "https://github.com/TaskBeacon/H000040-probabilistic-stimulus-selection",
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"default_branch": "main",
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"download_url": "https://github.com/TaskBeacon/H000040-probabilistic-stimulus-selection/archive/refs/heads/main.zip",
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"run_url": "https://taskbeacon.github.io/psyflow-web/?task=H000040-probabilistic-stimulus-selection",
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"last_updated": "2026-04-04T02:21:39Z"
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}
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]
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}

‎public/readmes/H000040-probabilistic-stimulus-selection.md‎

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# Probabilistic Stimulus Selection Task
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## Overview
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This snapshot mirrors the browser companion task `H000040-probabilistic-stimulus-selection`.
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It preserves the kana-based learning and transfer logic from the local canonical build while running inside the shared browser runner.
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## Task Flow
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1. Instructions explain the left/right response mapping.
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2. Learning trials present AB, CD, and EF pairs with probabilistic feedback.
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3. The learning block stops early only when the criterion is met.
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4. Transfer trials present all pairwise combinations without feedback.
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5. A final screen ends the task and exports the data.
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## Configuration
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- Six kana symbols are randomized across roles A-F per participant.
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- Learning probabilities are AB 80/20, CD 70/30, and EF 60/40.
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- Response keys are `A` for left and `L` for right.
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- The preview uses shortened counts so the browser version stays compact.
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## Run
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Open the TaskBeacon browser runner and launch `H000040-probabilistic-stimulus-selection`.

‎public/readmes/T000040-probabilistic-stimulus-selection.md‎

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# Probabilistic Stimulus Selection Task
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## Overview
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This snapshot mirrors the local canonical task `T000040-probabilistic-stimulus-selection`.
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Participants learn three kana-symbol pairs with probabilistic feedback and then complete a transfer block without feedback.
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## Task Flow
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1. Instructions explain the left/right response mapping.
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2. Learning trials present AB, CD, and EF pairs with correct/incorrect feedback.
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3. A criterion check decides whether learning is sufficient.
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4. Transfer trials present all pairwise combinations without feedback.
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5. A final screen ends the task and exports the data.
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## Configuration
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- Six kana symbols are randomized across roles A-F per participant.
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- Learning probabilities are AB 80/20, CD 70/30, and EF 60/40.
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- Response keys are `A` for left and `L` for right.
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- The preview and web companion use shortened counts for fast review.
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## Run
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Open the local TaskBeacon repository for `T000040-probabilistic-stimulus-selection`.

‎src/data/readmes/H000040-probabilistic-stimulus-selection.md‎

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# Probabilistic Stimulus Selection Task
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## Overview
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This snapshot mirrors the browser companion task `H000040-probabilistic-stimulus-selection`.
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It preserves the kana-based learning and transfer logic from the local canonical build while running inside the shared browser runner.
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## Task Flow
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1. Instructions explain the left/right response mapping.
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2. Learning trials present AB, CD, and EF pairs with probabilistic feedback.
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3. The learning block stops early only when the criterion is met.
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4. Transfer trials present all pairwise combinations without feedback.
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5. A final screen ends the task and exports the data.
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## Configuration
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- Six kana symbols are randomized across roles A-F per participant.
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- Learning probabilities are AB 80/20, CD 70/30, and EF 60/40.
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- Response keys are `A` for left and `L` for right.
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- The preview uses shortened counts so the browser version stays compact.
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## Run
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Open the TaskBeacon browser runner and launch `H000040-probabilistic-stimulus-selection`.

‎src/data/readmes/T000040-probabilistic-stimulus-selection.md‎

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# Probabilistic Stimulus Selection Task
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## Overview
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This snapshot mirrors the local canonical task `T000040-probabilistic-stimulus-selection`.
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Participants learn three kana-symbol pairs with probabilistic feedback and then complete a transfer block without feedback.
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## Task Flow
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1. Instructions explain the left/right response mapping.
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2. Learning trials present AB, CD, and EF pairs with correct/incorrect feedback.
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3. A criterion check decides whether learning is sufficient.
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4. Transfer trials present all pairwise combinations without feedback.
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5. A final screen ends the task and exports the data.
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## Configuration
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- Six kana symbols are randomized across roles A-F per participant.
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- Learning probabilities are AB 80/20, CD 70/30, and EF 60/40.
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- Response keys are `A` for left and `L` for right.
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- The preview and web companion use shortened counts for fast review.
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## Run
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Open the local TaskBeacon repository for `T000040-probabilistic-stimulus-selection`.

‎src/data/tasks_index.json‎

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"readme_run_anchor": "#run",
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"run_url": null,
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"web_variant": null
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},
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{
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"id": "T000040",
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"slug": "probabilistic-stimulus-selection",
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"title": "Probabilistic Stimulus Selection Task",
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"acquisition": "behavior",
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"variant": "baseline",
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"release_tag": "v0.1.0-dev",
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"repo": "T000040-probabilistic-stimulus-selection",
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"full_name": "TaskBeacon/T000040-probabilistic-stimulus-selection",
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"html_url": "https://github.com/TaskBeacon/T000040-probabilistic-stimulus-selection",
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"default_branch": "main",
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"short_description": "Kana-based probabilistic stimulus selection task with AB/CD/EF learning and transfer testing.",
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"maturity": "draft",
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"tags": {
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"paradigm": [],
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"response": [],
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"modality": [
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"behavior"
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],
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"language": [
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"Chinese"
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]
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},
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"keywords": [
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"probabilistic-stimulus-selection",
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"probabilistic",
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"stimulus",
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"selection"
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],
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"psyflow_version": "local checkout",
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"has_voiceover": false,
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"last_updated": "2026-04-04T02:21:39Z",
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"structure": {
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"config": true,
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"assets": true,
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"src": true
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},
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"readme_snapshot_path": "/readmes/T000040-probabilistic-stimulus-selection.md",
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"readme_run_anchor": "#run",
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"run_url": null,
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"web_variant": null
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}
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]
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}

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