{"id":"W1577122373","doi":"10.15353/joci.v8i2.3039","title":"Data Template For District Economic Planning","year":2012,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"Social and Economic Development in India","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Corporate governance; Politics; State (computer science); Set (abstract data type); Local governance; Regional science; Open data; Data set; Business; Geography; Computer science; Political science; Artificial intelligence","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":[0.002298506,0.0005934425,0.0005130366,0.003509393,0.001044006,0.003431184,0.001524348,0.0008038596,0.1627945],"category_scores_gemma":[0.01316014,0.0008115415,0.0008225929,0.008042069,0.0005344567,0.0023904,0.002258131,0.001658639,0.06394833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001841366,"about_ca_system_score_gemma":0.00446644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01263729,"about_ca_topic_score_gemma":0.01395895,"domain_scores_codex":[0.9981368,0.0004779195,0.0004053193,0.0003246701,0.00048546,0.0001698396],"domain_scores_gemma":[0.9940647,0.002058941,0.0003487364,0.002119934,0.001128784,0.0002788827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002448469,0.0001362671,0.004536868,0.000831319,0.00004072771,0.0004518718,0.001445438,0.009534547,0.001619538,0.1137347,0.7172288,0.150195],"study_design_scores_gemma":[0.00001878978,0.00000959121,0.001211034,0.00008415795,0.00000446462,0.00007562555,0.0002618895,0.001873278,0.00103174,0.009034933,0.9863753,0.00001924521],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004668069,0.0001604901,0.1517022,0.001499159,0.0008668756,0.001608083,0.6638858,0.01768787,0.1579215],"genre_scores_gemma":[0.04823969,0.0004316044,0.282826,0.0004818118,0.0001371476,0.004533415,0.5863303,0.007582454,0.06943753],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1627945,"threshold_uncertainty_score":0.5446019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.205376362075858,"score_gpt":0.3831191271626035,"score_spread":0.1777427650867455,"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."}}