{"id":"W2962808436","doi":"10.2196/12768","title":"Behavior Change Techniques Incorporated in Fitness Trackers: Content Analysis","year":2019,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Physical Activity and Health","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Activity tracker; BitTorrent tracker; Content analysis; Computer science; Physical activity; Artificial intelligence; Physical medicine and rehabilitation; Medicine; Eye tracking","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":[0.01639544,0.0004775592,0.0009042223,0.007167466,0.0008413458,0.00168194,0.000708317,0.0005452379,0.003006092],"category_scores_gemma":[0.05777244,0.0003709702,0.00137854,0.005457833,0.0005291604,0.001736622,0.001638165,0.0009440446,0.001114408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003016141,"about_ca_system_score_gemma":0.004620911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004210063,"about_ca_topic_score_gemma":0.007452442,"domain_scores_codex":[0.9881806,0.004073035,0.002385804,0.0007824263,0.004205784,0.0003723103],"domain_scores_gemma":[0.9395702,0.02939918,0.00998438,0.002366052,0.01779256,0.000887599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0007346466,0.001239919,0.2620636,0.01025013,0.0002623648,0.0001697716,0.0327444,0.0007955068,0.005140546,0.001461149,0.01969113,0.6654469],"study_design_scores_gemma":[0.0002566511,0.001045969,0.8983185,0.006155691,0.0003727704,0.0003592941,0.01355054,0.005612094,0.003378222,0.001328478,0.06941615,0.0002056212],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8628334,0.003227384,0.04197694,0.001795905,0.000344251,0.04538121,0.02242297,0.00132,0.02069801],"genre_scores_gemma":[0.6940425,0.005118451,0.2042802,0.0007326335,0.0001816461,0.0709653,0.01742033,0.0003999427,0.006859029],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01639544,"threshold_uncertainty_score":0.08670837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2239564722256535,"score_gpt":0.4314338384385663,"score_spread":0.2074773662129128,"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."}}