{"id":"W2793725623","doi":"10.1158/1538-7445.sabcs17-is-3","title":"Abstract IS-3: Breast Imaging in Resource Constrained Regions: Lessons from Uganda","year":2018,"lang":"en","type":"article","venue":"Cancer Research","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Breast cancer; Medicine; Cancer; Hormonal therapy; Breast lumps; Health care; Family medicine; Internal medicine; Economic growth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004675997,0.0007109095,0.00065142,0.001292804,0.004137246,0.005122001,0.001814351,0.002566354,0.01114101],"category_scores_gemma":[0.01786674,0.0004967201,0.0006646548,0.002487857,0.002086055,0.005695858,0.006017638,0.005739322,0.001502415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004555571,"about_ca_system_score_gemma":0.01289164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06343116,"about_ca_topic_score_gemma":0.07407801,"domain_scores_codex":[0.9973761,0.001626773,0.0001076413,0.00009698627,0.0001603342,0.000632158],"domain_scores_gemma":[0.99309,0.002789654,0.0005596355,0.0002615191,0.001805306,0.001494025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005046061,0.0003358342,0.0868974,0.005796705,0.0001745776,0.009973709,0.06165244,0.001294655,0.0003683415,0.02253542,0.3939925,0.4164738],"study_design_scores_gemma":[0.0001628125,0.0004925021,0.07381799,0.02873448,0.0002416795,0.006403212,0.2964318,0.001140278,0.0007087818,0.04740862,0.5442342,0.000223659],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1408232,0.07912989,0.00219472,0.6967076,0.004160657,0.0002820915,0.003060409,0.0001649549,0.0734765],"genre_scores_gemma":[0.7763386,0.1079703,0.00549109,0.09433758,0.002264355,0.0004730391,0.001757125,0.0003048013,0.01106321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06343116,"threshold_uncertainty_score":0.1261238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2242693075205816,"score_gpt":0.4861436604398952,"score_spread":0.2618743529193135,"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."}}