{"id":"W3199122764","doi":"10.1101/2021.09.16.458206","title":"Collective dynamics support group drumming, reduce variability, and stabilize tempo drift","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; McMaster University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Sociality; Dyad; Social dynamics; Dynamics (music); Psychology; Cognitive psychology; Crowds; Synchronization (alternating current); Task (project management); Group (periodic table); Communication; Social psychology; Cognitive science; Computer science; Mathematics; Artificial intelligence; Topology (electrical circuits); Physics; Engineering; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000268794,0.0002042442,0.0002122542,0.0002729643,0.0003081227,0.0004679715,0.0002463538,0.0003257829,0.003167654],"category_scores_gemma":[0.001712439,0.0001424901,0.0001961295,0.0001152959,0.0003431732,0.0004872934,0.0007310775,0.0003006599,0.0003091917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001788081,"about_ca_system_score_gemma":0.00017479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004533298,"about_ca_topic_score_gemma":0.0004502531,"domain_scores_codex":[0.9999106,0.00002465425,0.000004859675,0.00002416679,0.00001895142,0.00001674841],"domain_scores_gemma":[0.999409,0.0001894726,0.0001569708,0.00008706015,0.00006162695,0.00009587043],"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":[0.0006319358,0.0002516184,0.02026084,0.0002685569,0.0001038334,0.0002948998,0.0009309717,0.05004619,0.8670957,0.01313224,0.001660092,0.04532301],"study_design_scores_gemma":[0.0002511683,0.001223056,0.1196654,0.0000719983,0.000116713,0.0004317707,0.001325971,0.7174239,0.1049574,0.04707149,0.007366318,0.00009498593],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9616933,0.0001125777,0.0350344,0.0001699839,0.00003431856,0.00001719975,0.00004933085,0.0001920788,0.002696804],"genre_scores_gemma":[0.997006,0.00001858577,0.002550512,0.00001113319,0.000004973893,0.000009436828,0.00001455431,0.00001160588,0.0003731742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003167654,"threshold_uncertainty_score":0.01059687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02037052402115623,"score_gpt":0.2613903788328767,"score_spread":0.2410198548117204,"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."}}