{"id":"W6958287665","doi":"10.6084/m9.figshare.14870416.v1","title":"Additional file 3 of Why don’t illiterate women in rural, Northern Tanzania, access maternal healthcare?","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Population; Data file; Government (linguistics); Data collection; Race (biology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001665168,0.0005337149,0.0006954166,0.001605257,0.001036503,0.00108955,0.001418338,0.0009929092,0.8999975],"category_scores_gemma":[0.02957578,0.0004302654,0.0005505731,0.002853834,0.0002235129,0.001972341,0.0009881735,0.0009506996,0.1564143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001445158,"about_ca_system_score_gemma":0.002499101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03183826,"about_ca_topic_score_gemma":0.0415298,"domain_scores_codex":[0.9992605,0.0002274986,0.0001346058,0.0001004765,0.0001309288,0.0001459692],"domain_scores_gemma":[0.9820603,0.01260592,0.001187408,0.0005031311,0.003030625,0.0006125374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00009010245,0.00002594658,0.0006868737,0.0007786514,0.000005583206,0.00002562156,0.0000884792,0.00005957657,0.00001164606,0.0004919984,0.9932988,0.004436754],"study_design_scores_gemma":[0.003185601,0.0001549666,0.02603355,0.007224899,0.00008905824,0.0003905363,0.002190272,0.0008078252,0.0002411834,0.009629516,0.949957,0.00009565039],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0003994821,0.00004102239,0.0002287709,0.001082143,0.00008768678,0.0004174258,0.9883198,0.0001647219,0.009258942],"genre_scores_gemma":[0.02939289,0.0007866998,0.007045555,0.006776391,0.0005932964,0.01432191,0.8305681,0.001183592,0.1093316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8999975,"threshold_uncertainty_score":0.1426414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02079038889613727,"score_gpt":0.2780743059754283,"score_spread":0.257283917079291,"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."}}