{"id":"W2801421509","doi":"10.1002/acr.23583","title":"Discordance Between Population Impact of Musculoskeletal Disorders and Scientific Representation: A Bibliometric Study","year":2018,"lang":"en","type":"article","venue":"Arthritis Care & Research","topic":"Musculoskeletal Disorders and Rehabilitation","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"University Health Network","keywords":"Medicine; MEDLINE; Public health; Multidisciplinary approach; Geriatrics; Gerontology; Population; Neglect; Health care; Family medicine; Environmental health; Psychiatry; Pathology; Social science","routes":{"ca_aff":true,"ca_fund":true,"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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0009470461,0.000132196,0.0003104166,0.009028737,0.000416745,0.0001033162,0.000106201,0.00006414477,0.0001130897],"category_scores_gemma":[0.0006543166,0.0001082012,0.0001813545,0.02389518,0.0008852702,0.0003031055,0.0001243954,0.0002165961,0.00001698318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000842417,"about_ca_system_score_gemma":0.0001111336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003635058,"about_ca_topic_score_gemma":0.001581948,"domain_scores_codex":[0.9972762,0.0003154148,0.0003700508,0.0005406979,0.001125309,0.0003723114],"domain_scores_gemma":[0.9980623,0.0002362036,0.00007102179,0.0004832807,0.0009686626,0.000178607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004321555,0.0001601908,0.6699551,0.0001101877,0.00003380706,0.000001635674,0.002363139,7.875163e-7,0.0004614499,0.00003110696,0.0001035371,0.3267358],"study_design_scores_gemma":[0.001792312,0.005114278,0.9843371,0.0001202933,0.00002101691,0.000002275171,0.007875271,0.00002761987,0.00003160379,0.0005077532,0.00006807594,0.0001024052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939114,0.003701322,0.0000391683,0.0001377353,0.00009487052,0.001475339,0.00002398419,0.0000262805,0.000589932],"genre_scores_gemma":[0.9991353,0.0002617368,0.0001419568,0.000001337467,0.0001620249,0.00005817162,0.0001227179,0.0000218987,0.00009483933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3266334,"threshold_uncertainty_score":0.9968524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04316269775174697,"score_gpt":0.4532570699860192,"score_spread":0.4100943722342722,"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."}}