{"id":"W7011697549","doi":"","title":"“My Biggest Learning Curve:” Coaches’ Experiences of Working with Athletes who Menstruate","year":2023,"lang":"en","type":"article","venue":"","topic":"Menstrual Health and Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Athletes; Coaching; Menstruation; Variety (cybernetics); Qualitative research; Content analysis; Qualitative property","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":[],"consensus_categories":[],"category_scores_codex":[0.0002651328,0.0001230919,0.0002914754,0.0001386487,0.0001067157,0.00001001432,0.00006092141,0.00005249555,0.0001964795],"category_scores_gemma":[0.0001094627,0.00008464811,0.00003732332,0.0005940183,0.0001484288,0.00004635344,0.00003044159,0.0001552208,0.00005037986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001315648,"about_ca_system_score_gemma":0.0001087569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008208209,"about_ca_topic_score_gemma":0.00002110224,"domain_scores_codex":[0.9988149,0.00003858973,0.0002502554,0.0002208411,0.0003116457,0.0003637134],"domain_scores_gemma":[0.9993817,0.0001422712,0.00009376127,0.000146926,0.00005256387,0.000182843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005480647,0.0000923062,0.8905612,0.0006047025,0.00006901333,0.00006090254,0.0475423,0.0001359829,0.0006906887,0.001227397,0.001291969,0.05717548],"study_design_scores_gemma":[0.006332548,0.004030224,0.06077161,0.002399027,0.0001148573,0.0000769269,0.8833825,0.009172867,0.01561747,0.0001287365,0.01723589,0.0007373266],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631982,0.0001709692,0.00005816734,0.0003795734,0.00008588751,0.0001994289,3.278897e-7,0.0001636251,0.03574376],"genre_scores_gemma":[0.9953873,0.0001376537,0.0006780421,0.0002119134,0.00005183366,0.00003563184,0.00001391872,0.00001705081,0.003466655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8358402,"threshold_uncertainty_score":0.345185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08282309737098814,"score_gpt":0.3157159181110227,"score_spread":0.2328928207400345,"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."}}