{"id":"W3208755187","doi":"","title":"Teammate social ties and subgroup memberships: A season-long social network analysis in track and field","year":2021,"lang":"en","type":"article","venue":"Journal of Exercise, Movement, and Sport (SCAPPS refereed abstracts repository)","topic":"Sports, Gender, and Society","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Centrality; Cohesion (chemistry); Social psychology; Psychology; Group cohesiveness; Interpersonal ties; Event (particle physics); Perception; Social network analysis; Track and field athletics; Field (mathematics); Athletes; Sociology; Mathematics; Social capital; Statistics; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009602334,0.0001506411,0.000258798,0.002014237,0.001691291,0.000985726,0.000411053,0.0002785252,0.001672564],"category_scores_gemma":[0.0025676,0.0001295753,0.0002280996,0.002011722,0.0004115743,0.0006377146,0.00105973,0.0003428632,0.0001309898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001614661,"about_ca_system_score_gemma":0.001564084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2599619,"about_ca_topic_score_gemma":0.4190095,"domain_scores_codex":[0.999658,0.00007867833,0.00001671769,0.00007687145,0.00006943644,0.0001003339],"domain_scores_gemma":[0.9988557,0.0002258822,0.0002816261,0.00007386369,0.0002047211,0.0003582394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008672813,0.00006439177,0.9815494,0.00001782791,0.00005456344,0.00007404291,0.007496266,0.0002175673,0.0007239682,0.000286826,0.0004428142,0.008985591],"study_design_scores_gemma":[0.000001597274,0.00003165159,0.9918052,0.000004779853,0.00001389466,0.00002719848,0.006860163,0.0006715936,0.00005096579,0.00007893871,0.0004503931,0.000003616748],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993544,0.0000185317,0.0001391376,0.00001754502,0.000001515452,0.000009929336,0.0001132523,0.000001518376,0.0003439995],"genre_scores_gemma":[0.9990471,0.00002652773,0.0002059462,0.000004348631,0.000002486458,0.00001567674,0.0003359494,0.000001701137,0.0003602781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2599619,"threshold_uncertainty_score":0.5168974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01969390800171331,"score_gpt":0.2702965212367524,"score_spread":0.2506026132350391,"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."}}