{"id":"W4395005093","doi":"10.1177/08445621241247865","title":"Anti-Black Medical Gaslighting in Healthcare: Experiences of Black Women in Canada","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Nursing Research","topic":"Climate Change and Health Impacts","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Health care; Medical care; Medicine; Computer science; Data science; Family medicine; Economics; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003624059,0.00007623698,0.0002448355,0.0005116523,0.00007532323,0.00004235146,0.000355015,0.00007068933,0.001455699],"category_scores_gemma":[0.0005784989,0.00006834503,0.0000209336,0.001134493,0.0005316266,0.0001679663,0.00002029274,0.0007839259,0.0000144583],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01158529,"about_ca_system_score_gemma":0.007951505,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9204369,"about_ca_topic_score_gemma":0.9834396,"domain_scores_codex":[0.9969035,0.0002258131,0.0005036293,0.0001572824,0.001026955,0.001182811],"domain_scores_gemma":[0.9977724,0.0002585484,0.00005684921,0.000103343,0.00003480416,0.001774055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004649765,0.00005974918,0.3573042,0.0002903947,0.000004337813,0.005934143,0.49644,0.0002913328,0.0003189241,0.00008543832,0.05570329,0.08352172],"study_design_scores_gemma":[0.0008780477,0.0007614456,0.4513391,0.018003,0.000003278134,0.0004242194,0.5154517,0.004892617,0.0005451082,0.00418617,0.003132885,0.0003824072],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768316,0.0009309822,5.971436e-7,0.0202132,0.000336078,0.00009085835,0.000003812157,0.000001091775,0.001591785],"genre_scores_gemma":[0.9994555,0.0001987347,0.00001476453,0.000183971,0.00009274099,0.000002432169,4.996667e-7,0.00001021017,0.0000411763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09403493,"threshold_uncertainty_score":0.9994571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1282825439157562,"score_gpt":0.4206870021466058,"score_spread":0.2924044582308496,"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."}}