{"id":"W4308842213","doi":"10.3389/fpain.2022.1014793","title":"Distinct care trajectories among persons living with arthritic conditions: A two-year state sequence analysis","year":2022,"lang":"en","type":"article","venue":"Frontiers in Pain Research","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale; Centres Intégré Universitaires de Santé et de Services Sociaux; Université du Québec en Abitibi-Témiscamingue; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke; Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Sequence (biology); State (computer science); Gerontology; Medicine; Demography; Computer science; Biology; Genetics; Sociology; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004236024,0.0001336416,0.0003413179,0.001176546,0.0005398412,0.0000433354,0.0001524845,0.00003610738,0.0003411151],"category_scores_gemma":[0.00147298,0.0001171843,0.0001419046,0.002974129,0.0006981255,0.0001022049,0.00007440116,0.0008307513,0.000002514073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000712107,"about_ca_system_score_gemma":0.0003002144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007422458,"about_ca_topic_score_gemma":0.00123028,"domain_scores_codex":[0.995427,0.00232107,0.0002486891,0.0004371864,0.001053165,0.0005128615],"domain_scores_gemma":[0.9982056,0.0009820267,0.00004291533,0.0003710444,0.0002336916,0.0001647406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009099492,0.0001111322,0.9836305,0.0004028401,0.0002053399,0.00006070675,0.01170388,0.0007288316,0.00009424312,0.00005332243,0.001723781,0.001194443],"study_design_scores_gemma":[0.0006506694,0.0008060165,0.7649277,0.0002627066,0.00007781501,0.00000194022,0.2249614,0.007578117,0.000005914175,0.0003022052,0.0002507876,0.0001747276],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940093,0.0006667276,0.002277187,0.0003214336,0.00008891716,0.0009179711,0.00008400929,0.00005182471,0.001582606],"genre_scores_gemma":[0.995719,0.00001836604,0.002369418,0.00003679655,0.00003836851,0.000594662,0.0001793266,0.00002453909,0.001019546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2187028,"threshold_uncertainty_score":0.4778637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02332624879900114,"score_gpt":0.3357142517396109,"score_spread":0.3123880029406098,"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."}}