{"id":"W2257964071","doi":"10.11575/prism/13485","title":"The intersecting social worlds of MRI scientists and MS clinicians","year":2004,"lang":"en","type":"dissertation","venue":"PRISM (University of Calgary)","topic":"Interdisciplinary Research and Collaboration","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Psychology; Data science; Medicine; Computer 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":["sts"],"consensus_categories":[],"category_scores_codex":[0.01617079,0.0006436254,0.0007356216,0.004241541,0.03818369,0.02921411,0.001891068,0.00300244,0.004101006],"category_scores_gemma":[0.02354415,0.0006725227,0.0004069372,0.003667744,0.0618367,0.01088424,0.01868029,0.005624827,0.0004848539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02199041,"about_ca_system_score_gemma":0.03003195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08362799,"about_ca_topic_score_gemma":0.07883835,"domain_scores_codex":[0.9576241,0.03343458,0.000576851,0.001234644,0.003460811,0.003669042],"domain_scores_gemma":[0.9753125,0.01287501,0.002753178,0.0009268493,0.002345099,0.005787375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001464714,0.00002992859,0.002306411,0.00002274063,0.000007653156,0.0001919908,0.9695062,0.000035574,0.00009016095,0.02288099,0.0006604358,0.004253361],"study_design_scores_gemma":[0.000005204126,0.00001055296,0.001542883,0.000060084,0.000004106995,0.00006497082,0.9820947,0.00003281896,0.00003734489,0.005719418,0.01041808,0.000009741948],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8023897,0.005053455,0.002637219,0.04559623,0.0002976392,0.0001440695,0.00005757988,0.00001920226,0.1438048],"genre_scores_gemma":[0.9939277,0.001477696,0.0004496922,0.001229281,0.00004041326,0.00004797847,0.00001368091,0.000008958409,0.002804508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9618163,"threshold_uncertainty_score":0.1662825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03431719604897691,"score_gpt":0.3522045277234953,"score_spread":0.3178873316745183,"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."}}