{"id":"W4402195197","doi":"10.2196/51198","title":"Harnessing the Power of Complementarity Between Smart Tracking Technology and Associated Health Information Technologies: Longitudinal Study","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Loyola Marymount University","keywords":"Complementarity (molecular biology); Logistic regression; Medicine; Econometrics; Computer science; Economics; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01040073,0.0005387979,0.0006985725,0.001755879,0.001786546,0.002165611,0.001059055,0.001018572,0.004359115],"category_scores_gemma":[0.02461601,0.0005648774,0.002306372,0.002835851,0.0007973178,0.002407211,0.002775779,0.002661641,0.0007601956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001210805,"about_ca_system_score_gemma":0.003180394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02889983,"about_ca_topic_score_gemma":0.03380462,"domain_scores_codex":[0.993954,0.003131618,0.0006061452,0.0008855821,0.0006430239,0.0007795285],"domain_scores_gemma":[0.9809011,0.006757281,0.006871401,0.002000087,0.002475411,0.0009947058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001387208,0.0003117317,0.9910836,0.0001110418,0.0005318521,0.0001099346,0.001245223,0.0002609394,0.00007179524,0.0008491025,0.001128256,0.004157795],"study_design_scores_gemma":[0.00008844711,0.0009691224,0.9713312,0.0005733912,0.001441599,0.000338227,0.008481255,0.006132989,0.0004241779,0.003023815,0.007107301,0.00008843715],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872395,0.001818328,0.004244193,0.001303606,0.00006197448,0.0002112368,0.003076661,0.00002140698,0.00202293],"genre_scores_gemma":[0.9951541,0.0003671983,0.001409609,0.0004048958,0.00004363131,0.000261485,0.001642025,0.00001142837,0.0007054871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02889983,"threshold_uncertainty_score":0.05746323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2236088996781965,"score_gpt":0.5582366903774849,"score_spread":0.3346277906992884,"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."}}