{"id":"W4386828226","doi":"10.1007/s41666-023-00149-y","title":"Natural Language Processing to Classify Caregiver Strategies Supporting Participation Among Children and Youth with Craniofacial Microsomia and Other Childhood-Onset Disabilities","year":2023,"lang":"en","type":"article","venue":"Journal of Healthcare Informatics Research","topic":"Craniofacial Disorders and Treatments","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; McMaster University Medical Centre","funders":"National Institute on Disability, Independent Living, and Rehabilitation Research; National Institute of Dental and Craniofacial Research","keywords":"Support vector machine; Computer science; Naive Bayes classifier; Artificial intelligence; Machine learning; International Classification of Functioning, Disability and Health; Set (abstract data type); Random forest; Psychological intervention; Multinomial logistic regression; Natural language processing; Rehabilitation; Psychology; Medicine; Physical therapy","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":[0.001256658,0.0007453983,0.0003399064,0.002166344,0.0002659766,0.0007295844,0.0005233308,0.0005616123,0.001145596],"category_scores_gemma":[0.005005955,0.0001322841,0.0008584788,0.0008853944,0.000244967,0.0007181389,0.0004728461,0.0006455936,0.0005819718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007126704,"about_ca_system_score_gemma":0.0008373265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009437253,"about_ca_topic_score_gemma":0.01486352,"domain_scores_codex":[0.9992114,0.0003035195,0.0001026848,0.0001981658,0.0001134126,0.00007079322],"domain_scores_gemma":[0.9970734,0.002165278,0.0002631863,0.0001152861,0.0003149255,0.000067871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001252865,0.001380729,0.3752128,0.001545332,0.0003483833,0.002599682,0.00340273,0.02471818,0.0241497,0.001483267,0.0154571,0.5484492],"study_design_scores_gemma":[0.0001413385,0.0009495238,0.4068426,0.000441363,0.0003226772,0.003207173,0.006838133,0.5360039,0.01868264,0.006731533,0.01968267,0.0001564239],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9441025,0.001095595,0.0345271,0.0007221229,0.00007415943,0.0004186882,0.01557895,0.001120367,0.00236048],"genre_scores_gemma":[0.9223529,0.0003393999,0.0473159,0.0001589851,0.00003533553,0.0004800417,0.02830481,0.00003365719,0.0009790029],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009437253,"threshold_uncertainty_score":0.01876467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02578545027002345,"score_gpt":0.3817043173653624,"score_spread":0.3559188670953389,"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."}}