{"id":"W1993720179","doi":"10.1016/j.actpsy.2006.11.003","title":"End-point focus manipulations to determine what information is used during observational learning","year":2007,"lang":"en","type":"article","venue":"Acta Psychologica","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Observational study; Focus (optics); Observational learning; Psychology; Point (geometry); End point; Cognitive psychology; Communication; Computer science; Medicine; Physics; Mathematics; Mathematics education; Optics; Experiential learning; Geometry","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005683888,0.0002108806,0.0001836205,0.0003385893,0.000376809,0.0001909386,0.0002252703,0.0002329271,0.01146962],"category_scores_gemma":[0.0001922997,0.0002096701,0.00008449076,0.0006926209,0.00003393152,0.001930101,0.00004947735,0.0002919882,0.001676608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001376669,"about_ca_system_score_gemma":0.000016174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002224043,"about_ca_topic_score_gemma":0.00002170257,"domain_scores_codex":[0.9981118,0.00008597082,0.0006842125,0.0003524935,0.0003549089,0.0004105452],"domain_scores_gemma":[0.998737,0.0001785919,0.0003069597,0.0003905042,0.0002229582,0.0001639881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001112068,0.0009016286,0.5942866,0.00004805517,0.000279882,0.00005016854,0.04360543,0.001059424,0.02431011,0.01761624,0.04206414,0.2746663],"study_design_scores_gemma":[0.0008605639,0.0001362432,0.9172524,0.00001915544,0.00001056654,0.00003339014,0.002130421,0.0001491105,0.0006097373,0.0002657488,0.07827315,0.0002595632],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9040549,0.000024907,0.06927256,0.007514718,0.001158405,0.0005002966,0.000007295704,0.000335727,0.01713119],"genre_scores_gemma":[0.9900205,0.00001860735,0.001838647,0.005294657,0.0002226858,0.0000558122,0.0001607983,0.00002177871,0.002366475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3229658,"threshold_uncertainty_score":0.9991007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1086607370083271,"score_gpt":0.3540543424044835,"score_spread":0.2453936053961564,"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."}}