{"id":"W3215448271","doi":"10.1177/20552076211056156","title":"Identifying technology industry-led initiatives to address digital health equity","year":2021,"lang":"en","type":"review","venue":"Digital Health","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health; Western University","funders":"Centre for Addiction and Mental Health","keywords":"CINAHL; Business; Health equity; Health information technology; Equity (law); Health technology; Grey literature; Digital health; Health care; Public relations; MEDLINE; Economic growth; Political science; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006354484,0.0007328819,0.003999431,0.001288618,0.0003048582,0.000302596,0.0003508773,0.0006800801,0.000113297],"category_scores_gemma":[0.0008404344,0.0006549393,0.000381995,0.002415905,0.0001182086,0.000633694,0.0006239539,0.002064721,0.0001898328],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001654091,"about_ca_system_score_gemma":0.008823684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008348181,"about_ca_topic_score_gemma":0.00004558303,"domain_scores_codex":[0.9939044,0.0001478626,0.002485496,0.00107636,0.0008408909,0.001544962],"domain_scores_gemma":[0.9958814,0.0002556967,0.001296866,0.0008000523,0.0002556332,0.001510344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001175142,0.0002174405,0.0003931315,0.0315681,0.0001399441,0.00009254381,0.0003368491,2.465202e-8,1.235096e-8,0.0006448719,0.008789155,0.9578062],"study_design_scores_gemma":[0.0009298859,0.001603878,0.0002560519,0.03680715,0.00009053796,0.0005212816,0.001657012,3.066649e-7,5.46912e-7,0.00009653355,0.9576368,0.0004000206],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001147575,0.9804865,0.0004067556,0.00835359,0.0005729283,0.004079176,0.001590226,0.0003863792,0.004009673],"genre_scores_gemma":[0.003297586,0.9816157,0.0003085243,0.005760511,0.0007361027,0.0003589904,0.007250156,0.0001627404,0.0005097354],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9574062,"threshold_uncertainty_score":0.9995902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2018762110356636,"score_gpt":0.527094218092073,"score_spread":0.3252180070564094,"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."}}