{"id":"W3028588294","doi":"10.2139/ssrn.3573193","title":"Mobile Health Behavior Tracking: Health Effects of Tracking Consistency and Its Prediction","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Tracking (education); Consistency (knowledge bases); Computer science; Artificial intelligence; Econometrics; Psychology; Mathematics","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":[0.008620033,0.0005112323,0.0005761972,0.001005098,0.0005274975,0.001796716,0.00105609,0.002276165,0.00523],"category_scores_gemma":[0.04512457,0.0004895406,0.001046074,0.001241841,0.0006344486,0.001543785,0.0009678187,0.001843355,0.0007476264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005105739,"about_ca_system_score_gemma":0.000541423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01140349,"about_ca_topic_score_gemma":0.006901521,"domain_scores_codex":[0.9971186,0.001572484,0.0001932148,0.0006597788,0.0002494017,0.0002066773],"domain_scores_gemma":[0.923458,0.06010002,0.007839207,0.005088106,0.001903369,0.001611231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001502167,0.0003891345,0.9898859,0.00001630526,0.0003452577,0.00003307522,0.0001302752,0.001123681,0.0002114866,0.0002998495,0.0003139167,0.005748969],"study_design_scores_gemma":[0.00005709321,0.0005668574,0.9787197,0.00001802483,0.0004754994,0.00008293034,0.0001154776,0.0184872,0.0003405797,0.0007803162,0.0003383969,0.00001796336],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992749,0.0004881437,0.003059133,0.000512154,0.00007203917,0.0000440541,0.00110572,0.00005741289,0.001912206],"genre_scores_gemma":[0.9980902,0.00005503157,0.0004896015,0.00007762435,0.0000425563,0.00001908128,0.0004936201,0.00001275269,0.0007195039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01140349,"threshold_uncertainty_score":0.04558766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02011916914316668,"score_gpt":0.2618781147487387,"score_spread":0.241758945605572,"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."}}