{"id":"W3175546393","doi":"10.1096/fasebj.2019.33.1_supplement.439.1","title":"The Big Q: Evaluating a Large‐Scale, Cross‐Disciplinary Anatomy and Physiology Course Using Q‐Methodology","year":2019,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Q Methodology Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Likert scale; Scale (ratio); Discipline; Course (navigation); Medical education; Diversity (politics); Course evaluation; Class (philosophy); Mathematics education; Psychology; Computer science; Higher education; Medicine; Engineering; Sociology; Artificial intelligence","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":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.04500463,0.0001784252,0.0003881662,0.0001302657,0.002597373,0.0003287004,0.001416376,0.0001568072,0.0002854136],"category_scores_gemma":[0.004160764,0.00008607875,0.0001521901,0.0005916681,0.0009652108,0.0001831881,0.0006286055,0.0009117328,0.0002051973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003912648,"about_ca_system_score_gemma":0.0002871957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005303488,"about_ca_topic_score_gemma":0.00002590731,"domain_scores_codex":[0.9902752,0.00715037,0.0007965374,0.0004560346,0.0007334286,0.0005884351],"domain_scores_gemma":[0.9769261,0.02071829,0.0007716563,0.000976279,0.0004693658,0.0001382439],"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":[0.0005880303,0.00012459,0.1456029,0.000007607395,0.0001956812,0.00001450387,0.007690479,0.004549553,0.7565621,0.006187668,0.001041015,0.0774359],"study_design_scores_gemma":[0.001667885,0.0002682688,0.4858931,0.00002550413,0.0001299959,0.003027857,0.01375738,0.07392772,0.004009726,0.415231,0.001746145,0.0003154129],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9603509,0.001186319,0.03336176,0.003165754,0.00124709,0.0002886841,0.00001017662,0.00001623304,0.000373062],"genre_scores_gemma":[0.963252,0.00005815004,0.03490425,0.0004870096,0.0004914461,0.00001252889,7.992621e-7,0.00001857589,0.0007752155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7525523,"threshold_uncertainty_score":0.9987011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4060756127096817,"score_gpt":0.5589422838295589,"score_spread":0.1528666711198772,"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."}}