{"id":"W2513265059","doi":"10.2196/mhealth.5961","title":"The Quality and Accuracy of Mobile Apps to Prevent Driving After Drinking Alcohol","year":2016,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queensland University of Technology","keywords":"Mobile apps; Quality (philosophy); Alcohol consumption; mHealth; Mobile device; Computer science; Internet privacy; Alcohol; Environmental health; Applied psychology; Psychology; Medicine; Psychiatry; World Wide Web; Psychological intervention","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":[0.03599967,0.0006023358,0.001657755,0.005518771,0.000535229,0.004418982,0.001145962,0.00122761,0.002389446],"category_scores_gemma":[0.2361051,0.0004823508,0.003031633,0.002991856,0.0008198942,0.003461735,0.001723518,0.001416046,0.0004643305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001154603,"about_ca_system_score_gemma":0.003881804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00334697,"about_ca_topic_score_gemma":0.006080816,"domain_scores_codex":[0.9650311,0.01492034,0.008077073,0.001647673,0.009792889,0.0005309574],"domain_scores_gemma":[0.7336468,0.213162,0.02375545,0.00329029,0.02532488,0.0008205275],"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":[0.001220945,0.0001886781,0.04435962,0.153194,0.003593227,0.0002137461,0.003583937,0.0004767537,0.0008440602,0.001381715,0.008793015,0.7821503],"study_design_scores_gemma":[0.0008431982,0.003401432,0.1775939,0.6007106,0.0367823,0.002652425,0.005228162,0.003843488,0.005597769,0.005378494,0.1574967,0.0004714741],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1349587,0.8163818,0.008619774,0.01096657,0.001436437,0.002590447,0.004974035,0.000345585,0.01972658],"genre_scores_gemma":[0.6640586,0.2981739,0.02697997,0.00351512,0.0006559059,0.002711436,0.002219448,0.0001307053,0.001554864],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03599967,"threshold_uncertainty_score":0.1903867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06544409126131738,"score_gpt":0.4237436964633501,"score_spread":0.3582996052020327,"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."}}