{"id":"W2799482137","doi":"10.2196/mhealth.9661","title":"Lessons From the Dot Contraceptive Efficacy Study: Analysis of the Use of Agile Development to Improve Recruitment and Enrollment for mHealth Research","year":2018,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"mHealth; Fertility; Pregnancy; Agile software development; Medicine; Assisted reproductive technology; Longitudinal study; Gynecology; Population; Family medicine; Computer science; Psychological intervention; Nursing; Infertility; Environmental health","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2360202,0.0009148503,0.0009292283,0.00181043,0.001884992,0.004844892,0.001977824,0.001534738,0.002717509],"category_scores_gemma":[0.4492888,0.000836466,0.001780529,0.002245058,0.002866699,0.005593457,0.005131523,0.003684508,0.0004157549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004693218,"about_ca_system_score_gemma":0.01187943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00585531,"about_ca_topic_score_gemma":0.01043488,"domain_scores_codex":[0.7914752,0.1708505,0.008927225,0.003782137,0.02181864,0.003146356],"domain_scores_gemma":[0.3102376,0.5958154,0.02396643,0.02250812,0.04186133,0.005611182],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001997645,0.003189847,0.2605474,0.004117279,0.0008904435,0.0008161963,0.08270844,0.001695118,0.0007419036,0.01381114,0.02454334,0.6049412],"study_design_scores_gemma":[0.003247217,0.02281394,0.5541955,0.0157452,0.002894781,0.002345997,0.1369068,0.02668131,0.007443566,0.02918904,0.1979275,0.0006090638],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8099288,0.005727712,0.07980648,0.05757118,0.0008560256,0.01088653,0.00171909,0.0004602069,0.03304398],"genre_scores_gemma":[0.9167725,0.00215842,0.06153037,0.009469926,0.0002818966,0.006838711,0.000528272,0.0003268316,0.002093053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7639798,"threshold_uncertainty_score":0.9421231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4745470285226173,"score_gpt":0.583998719241822,"score_spread":0.1094516907192047,"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."}}