{"id":"W2956210777","doi":"10.2196/14724","title":"Reimbursement of Apps for Mental Health: Findings From Interviews","year":2019,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reimbursement; Payment; Mental health; Current Procedural Terminology; Medical prescription; Health care; Stakeholder; Medicine; Business; Family medicine; Internet privacy; Nursing; Public relations; Psychiatry; Computer science; Finance; 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":[0.01813202,0.0006825139,0.0004648019,0.002083748,0.005268851,0.003618946,0.001266932,0.002205989,0.001863122],"category_scores_gemma":[0.05518141,0.0008071024,0.000389855,0.002028275,0.004322087,0.004299102,0.007058135,0.002677492,0.0003993991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005006406,"about_ca_system_score_gemma":0.006238219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01162733,"about_ca_topic_score_gemma":0.01289338,"domain_scores_codex":[0.9738491,0.01934714,0.001124309,0.001008108,0.001915027,0.00275623],"domain_scores_gemma":[0.913519,0.07340492,0.006385775,0.0007039224,0.003764914,0.00222154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004971484,0.00004616625,0.009562056,0.0001950218,0.000005866408,0.0006918398,0.9792363,0.00005585785,0.000577532,0.0006814742,0.0008684346,0.008029621],"study_design_scores_gemma":[0.00000492971,0.00003209076,0.00534504,0.0003511502,0.000007598622,0.0002398998,0.9858792,0.0001829214,0.0003152654,0.0002136596,0.007411231,0.00001693853],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827288,0.0009945593,0.003378715,0.003590194,0.00005395807,0.0003346987,0.0004903326,0.00002335053,0.008405366],"genre_scores_gemma":[0.9927597,0.001400338,0.001543935,0.001795711,0.00003241229,0.0005168076,0.0001545023,0.00002203557,0.001774615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01813202,"threshold_uncertainty_score":0.09589243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0593901068852485,"score_gpt":0.4468069135958793,"score_spread":0.3874168067106308,"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."}}