{"id":"W2524075940","doi":"","title":"THE STATUS OF WOMEN IN THE SURVEYING AND MAPPING WORLD","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Cartography; Regional science; Library science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001411251,0.00009920285,0.0001071161,0.001714414,0.001045872,0.001032698,0.0002007422,0.0001996524,0.004926859],"category_scores_gemma":[0.00430494,0.00009181196,0.00009039117,0.002164993,0.0005854825,0.001102273,0.0006907037,0.0002662826,0.0006257622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003611694,"about_ca_system_score_gemma":0.0005242749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03353357,"about_ca_topic_score_gemma":0.07046854,"domain_scores_codex":[0.9993812,0.0003235954,0.00002998295,0.00005545412,0.00007695562,0.00013271],"domain_scores_gemma":[0.9985501,0.0004196549,0.0003576156,0.0001061984,0.0003622644,0.0002042294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009855052,0.00002254531,0.9114801,0.00006916064,0.00001793404,0.00009558296,0.02914616,0.00006607542,0.0009630888,0.003458468,0.006048148,0.04853416],"study_design_scores_gemma":[0.000002734603,0.00007374019,0.8799392,0.00009903814,0.00001326228,0.0001893094,0.0772607,0.0001697093,0.0007549694,0.00060967,0.04087054,0.00001711174],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9724449,0.0008259827,0.0004270502,0.002151452,0.00005011878,0.00001411763,0.001798802,0.000008868504,0.02227869],"genre_scores_gemma":[0.9895215,0.0007818062,0.0002864089,0.0001356022,0.00001727103,0.00001699183,0.0004619155,0.000006326232,0.008772201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03353357,"threshold_uncertainty_score":0.0666768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02248299325226807,"score_gpt":0.267014926502185,"score_spread":0.2445319332499169,"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."}}