{"id":"W2073129483","doi":"10.3138/carto.47.2.80","title":"Theorizing Indigital Geographic Information Networks","year":2012,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indigenous; Geospatial analysis; Dichotomy; Technoscience; Geographic information system; Construct (python library); Geography; Traditional knowledge; Data science; Sociology; Epistemology; Social science; Computer science; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.005087997,0.0003093657,0.0002631465,0.00179876,0.003407036,0.002266806,0.0006792322,0.0002722949,0.00004647025],"category_scores_gemma":[0.0008264802,0.0002460827,0.000385161,0.001286559,0.0006100122,0.0129035,0.0001406049,0.0003976552,0.00002020385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007142158,"about_ca_system_score_gemma":0.0001154094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000370804,"about_ca_topic_score_gemma":0.0001211317,"domain_scores_codex":[0.9962288,0.0001925204,0.001285146,0.0001191551,0.001381651,0.0007927887],"domain_scores_gemma":[0.9951799,0.0003707795,0.001140766,0.0002102891,0.002770658,0.0003275936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001363173,0.00005388153,0.17652,0.00003900816,0.0005106559,3.474491e-7,0.04084933,0.0003491936,0.00000229582,0.7498752,0.003196547,0.02846722],"study_design_scores_gemma":[0.001256366,0.00007605903,0.03970348,0.00007881416,0.0001042972,0.000109346,0.03340687,0.001485256,0.000006111996,0.005609758,0.9177069,0.0004567418],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4089635,0.004685972,0.4538381,0.02393742,0.04415004,0.007942679,0.0004397356,0.00143005,0.05461248],"genre_scores_gemma":[0.9918084,0.003387312,0.0001638233,0.00287715,0.00113469,0.0001680398,0.0003904589,0.00001450257,0.00005568293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9145104,"threshold_uncertainty_score":0.9999992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01400149969548626,"score_gpt":0.3015456046812316,"score_spread":0.2875441049857453,"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."}}