{"id":"W2953086004","doi":"","title":"Women and Mine Development: Capturing Vulnerability Using Open Data and GIS","year":2015,"lang":"en","type":"article","venue":"2015-Sustainable Industrial Processing Summit","topic":"Mining and Resource Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vulnerability (computing); Geography; Environmental planning; Work (physics); Environmental resource management; Engineering; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002179972,0.000280469,0.0003635718,0.0001588436,0.0003462168,0.0008322234,0.00067614,0.0001951465,0.00001366978],"category_scores_gemma":[0.0003847851,0.0002662439,0.000008327711,0.0003113346,0.0001111344,0.0008031426,0.001869579,0.0003550847,0.000002746043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004409729,"about_ca_system_score_gemma":0.000346229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003132533,"about_ca_topic_score_gemma":0.00001464808,"domain_scores_codex":[0.9980397,0.00006507104,0.0003959181,0.0005339761,0.0002642631,0.0007010647],"domain_scores_gemma":[0.9989404,0.00003231574,0.00009127372,0.0004712647,0.0001128253,0.0003518967],"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":[0.0005438338,0.0002929679,0.03876782,0.004523241,0.0005937941,0.0003842998,0.05505876,0.03122696,0.0001779408,0.0001774263,0.05217437,0.8160786],"study_design_scores_gemma":[0.006237287,0.0001255656,0.000782682,0.0004969919,0.0001177117,0.00002657495,0.08894631,0.1402609,0.0002585025,0.0005476317,0.7606946,0.001505241],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901072,0.001609613,0.0006914375,0.0001694176,0.0001520058,0.0005385025,0.00000784592,0.0001896303,0.006534362],"genre_scores_gemma":[0.9930308,0.000007561125,0.002805396,0.00002526737,0.0002876209,0.00003334195,0.00002714876,0.00005700277,0.003725879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8145733,"threshold_uncertainty_score":0.999979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1206583821329066,"score_gpt":0.295495912514355,"score_spread":0.1748375303814484,"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."}}