{"id":"W2264823080","doi":"10.3389/fpsyg.2016.00051","title":"Observational Learning: Tell Beginners What They Are about to Watch and They Will Learn Better","year":2016,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Task (project management); Psychology; Observational learning; Observational study; Motor learning; Quality (philosophy); Test (biology); Cognitive psychology; Observer (physics); Applied psychology; Mathematics education; Experiential learning; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002228664,0.0001453151,0.0002040449,0.0001294986,0.00008380126,0.00005677234,0.0002235226,0.0001181099,0.00004953082],"category_scores_gemma":[0.0003396542,0.0001063656,0.00003715959,0.00008523322,0.0001060191,0.0005189215,0.00004041824,0.0001903126,0.00005454676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000318288,"about_ca_system_score_gemma":0.00001158774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001220765,"about_ca_topic_score_gemma":0.00002853996,"domain_scores_codex":[0.9984939,0.0002320204,0.0002145146,0.000554039,0.0001672046,0.0003383427],"domain_scores_gemma":[0.9994257,0.0001459076,0.0001005236,0.0002079164,0.0000286485,0.00009127135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004110755,0.0001010865,0.4863248,0.00001028223,0.00001513637,0.00003854384,0.001689099,0.0001035699,0.09810869,0.001451366,0.01396369,0.3977827],"study_design_scores_gemma":[0.002599459,0.0002668138,0.4713538,0.0001189606,0.000009740703,0.00002009621,0.000410868,0.0004082654,0.0005528711,0.03145634,0.4923856,0.0004172134],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.900139,0.0001714599,0.02462509,0.07091499,0.002590443,0.0003310387,0.000007416543,0.00006514281,0.001155431],"genre_scores_gemma":[0.984603,0.0005182992,0.001872468,0.01090279,0.000159473,0.00004453445,0.000002241411,0.00002344839,0.001873734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4784219,"threshold_uncertainty_score":0.4337463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0375376542502513,"score_gpt":0.2878210376641634,"score_spread":0.2502833834139121,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}