{"id":"W2068616628","doi":"10.3138/1341-21jt-4p83-1651","title":"Women and GIS: Geospatial Technologies and Feminist Geographies","year":2005,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Variety (cybernetics); Everyday life; Geographic information system; Sociology; Feminization (sociology); Feminism; Data science; Geography; Computer science; Gender studies; Political science; Cartography","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003969814,0.0006219023,0.0003164499,0.002498579,0.004475502,0.009242365,0.0006093165,0.001791186,0.008533197],"category_scores_gemma":[0.003893519,0.0002712904,0.0002209615,0.002816482,0.0302859,0.009206125,0.004705285,0.001754832,0.0005801404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003240824,"about_ca_system_score_gemma":0.001220543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004355507,"about_ca_topic_score_gemma":0.005003557,"domain_scores_codex":[0.9964384,0.002825179,0.0000384307,0.0001926958,0.000281115,0.0002241507],"domain_scores_gemma":[0.9963247,0.003016358,0.000260659,0.000115793,0.0001330288,0.0001493648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002510332,0.00001293138,0.00207106,0.0001246583,0.000007516416,0.000294186,0.1631718,0.0001958799,0.0002553912,0.8043036,0.007335933,0.02220188],"study_design_scores_gemma":[0.000010427,0.0000251955,0.002213272,0.0005229969,0.000009244523,0.0005219959,0.2402836,0.0003859005,0.0006005953,0.2708968,0.4845088,0.00002122935],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1336519,0.04781023,0.02276048,0.2148777,0.001194281,0.00003707286,0.0003608732,0.0001343117,0.5791731],"genre_scores_gemma":[0.9548845,0.01321416,0.002089962,0.00353603,0.0005734598,0.00005313531,0.00005566276,0.00009611638,0.02549692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9955245,"threshold_uncertainty_score":0.02854645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01257426907140793,"score_gpt":0.2912384918040705,"score_spread":0.2786642227326626,"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."}}