{"id":"W2765847033","doi":"10.2196/formative.5151","title":"Using mHealth to Support Postabortion Contraceptive Use: Results From a Feasibility Study in Urban Bangladesh","year":2017,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Government of the United Kingdom","keywords":"mHealth; Mobile phone; Abortion; Business; Equity (law); Population; Family planning; Developing country; Pregnancy; Medicine; Internet privacy; Computer science; Health care; Economic growth; Environmental health; Telecommunications; Economics; Research methodology; Political science","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":[0.00512555,0.0007949849,0.0006409675,0.0007623459,0.001866494,0.000831697,0.0007312953,0.001054227,0.003645876],"category_scores_gemma":[0.00687731,0.0006975968,0.0006797107,0.0009146098,0.001010736,0.0008786031,0.001064155,0.0008080278,0.001085855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001505257,"about_ca_system_score_gemma":0.003363553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02293503,"about_ca_topic_score_gemma":0.03043527,"domain_scores_codex":[0.9969597,0.001708422,0.0002622934,0.0002038831,0.0003698852,0.0004959457],"domain_scores_gemma":[0.9950541,0.002134952,0.0006134288,0.000213878,0.00113179,0.0008519354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01436515,0.08307935,0.6681808,0.003146172,0.0003069893,0.005317123,0.08275121,0.0006875093,0.02169707,0.0005338491,0.001960052,0.1179748],"study_design_scores_gemma":[0.005687562,0.1247533,0.7458084,0.0004373383,0.0003994383,0.001369632,0.1124434,0.0008720276,0.003277816,0.0002390019,0.004492993,0.0002190314],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960473,0.00006086241,0.0002440571,0.0001732068,0.000004546165,0.002285843,0.000211551,0.000007091659,0.0009655718],"genre_scores_gemma":[0.9916762,0.000597523,0.001669019,0.0003099515,0.00001292522,0.004338833,0.0003322486,0.000009538605,0.001053839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02293503,"threshold_uncertainty_score":0.0456031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4036926372848644,"score_gpt":0.6124594114389132,"score_spread":0.2087667741540488,"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."}}