{"id":"W4205827219","doi":"10.3389/fpsyg.2021.706004","title":"Extension of Dancer’s Legs: Increasing Angles Show Motion","year":2022,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Università degli Studi Roma Tre","keywords":"Movement (music); Psychology; Motion (physics); Range of motion; Extension (predicate logic); Animation; Perception; Range (aeronautics); Front (military); Action (physics); Communication; Artificial intelligence; Cognitive psychology; Computer vision; Physical medicine and rehabilitation; Computer science; Computer graphics (images); Physics; Acoustics; Engineering; Physical therapy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001537215,0.0003006043,0.0001725604,0.0002988948,0.0001343255,0.0004097356,0.0001230209,0.0002656565,0.007555271],"category_scores_gemma":[0.001820017,0.0001686634,0.0001462326,0.0001410183,0.0003259659,0.0003576707,0.0004507732,0.0004484541,0.0003094731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001248894,"about_ca_system_score_gemma":0.00005974618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000439532,"about_ca_topic_score_gemma":0.001061465,"domain_scores_codex":[0.9998987,0.00002156809,0.000005070973,0.00003409658,0.00002511031,0.00001542843],"domain_scores_gemma":[0.9993795,0.0002442839,0.0001457094,0.0000589784,0.0000440786,0.0001274705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00134223,0.0001677759,0.02562837,0.0002508005,0.00005380968,0.0003421462,0.001569159,0.0002469,0.9386187,0.0004338448,0.0007239454,0.03062238],"study_design_scores_gemma":[0.00007590209,0.001147521,0.9596418,0.00004991824,0.00006552506,0.0008117539,0.001248524,0.001133623,0.03296556,0.0006981039,0.002136542,0.0000253284],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915012,0.0001228338,0.001219036,0.00007873036,0.00002138443,0.00001430334,0.0001161672,0.00004980101,0.006876418],"genre_scores_gemma":[0.9963074,0.00008784041,0.001972257,0.00007747993,0.00001178855,0.00001596442,0.0001937132,0.00002974456,0.001303817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007555271,"threshold_uncertainty_score":0.02527493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03816490174070229,"score_gpt":0.3302687040779765,"score_spread":0.2921038023372742,"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."}}