{"id":"W4281649170","doi":"10.1016/j.asmr.2022.04.020","title":"Automated 3D Analysis of Clinical Magnetic Resonance Images Demonstrates Significant Reductions in Cam Morphology Following Arthroscopic Intervention in Contrast to Physiotherapy","year":2022,"lang":"en","type":"article","venue":"Arthroscopy Sports Medicine and Rehabilitation","topic":"Hip disorders and treatments","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Bone and Joint Health Institute","funders":"Medical Research Council; Australian e-Health Research Centre; University of Queensland; National Health and Medical Research Council; Pfizer; Eli Lilly and Company","keywords":"Magnetic resonance imaging; Contrast (vision); Medicine; Morphology (biology); Intervention (counseling); Physical therapy; Physical medicine and rehabilitation; Radiology; Computer science; Artificial intelligence; Biology; Nursing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007655596,0.0002798159,0.0007385066,0.0005969913,0.0001705085,0.000428044,0.0003387901,0.0002616694,0.001462338],"category_scores_gemma":[0.002433676,0.0002678958,0.0002508544,0.0004065642,0.0004235848,0.0001964831,0.0004057095,0.0002230737,0.000233207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002182978,"about_ca_system_score_gemma":0.0003007293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001896624,"about_ca_topic_score_gemma":0.003601172,"domain_scores_codex":[0.9993815,0.000219161,0.00003870142,0.00007898628,0.0002339563,0.00004760364],"domain_scores_gemma":[0.9990453,0.0001786165,0.0004444511,0.00008827908,0.0001552803,0.00008803897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01978093,0.001702016,0.4617464,0.0009114509,0.0006225423,0.0009978391,0.001086405,0.00591984,0.2010169,0.0002116225,0.001981449,0.3040226],"study_design_scores_gemma":[0.0002631054,0.003304689,0.9882719,0.00001319574,0.00005501101,0.0005753743,0.0000936943,0.002879189,0.003832125,0.00005505142,0.0006383454,0.00001839023],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972686,0.0002873219,0.001472846,0.00003370717,0.000009517503,0.00007905445,0.0001078514,0.00003056827,0.0007106407],"genre_scores_gemma":[0.9967572,0.0001345247,0.002224137,0.00004582649,0.00001678475,0.00007613536,0.0002091492,0.00000721817,0.0005290917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001896624,"threshold_uncertainty_score":0.004891992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01207122843293835,"score_gpt":0.3727830344087596,"score_spread":0.3607118059758213,"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."}}