{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.03445238,0.0006950172,0.002648429,0.1350256,0.001352945,0.007151163,0.001635179,0.001094707,0.003223163],"category_scores_gemma":[0.2173757,0.000478471,0.002595213,0.1916801,0.002056642,0.005073518,0.005190272,0.0005917056,0.0005883048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002922765,"about_ca_system_score_gemma":0.004737956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00430371,"about_ca_topic_score_gemma":0.005274947,"domain_scores_codex":[0.9469122,0.01097207,0.01927616,0.004080486,0.01745562,0.001303358],"domain_scores_gemma":[0.7054218,0.1790494,0.07501488,0.009686237,0.02831297,0.002514755],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003210654,0.0000706951,0.9184768,0.01508792,0.004276025,0.0003603133,0.003547264,0.0005377366,0.0005990631,0.001890784,0.003845586,0.05098684],"study_design_scores_gemma":[0.00006686891,0.0000954135,0.9744526,0.002870005,0.002521785,0.0009490366,0.004464545,0.001289346,0.0003512422,0.002398819,0.01046015,0.00008018455],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8640917,0.06640438,0.003257254,0.005382958,0.000263965,0.0007675798,0.04651059,0.0002500799,0.01307143],"genre_scores_gemma":[0.9683391,0.01329787,0.002847433,0.0002816473,0.0003283308,0.0005960676,0.01387138,0.00004727266,0.0003909289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9655476,"threshold_uncertainty_score":0.1822038,"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."}}