{"id":"W4366549947","doi":"10.1145/3544548.3580868","title":"Governor: Turning Open Government Data Portals into Interactive Databases","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Upload; Governor; Computer science; World Wide Web; Open data; Government (linguistics); Database; TRACE (psycholinguistics); Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.00858006,0.0001483179,0.0002793194,0.00007539764,0.0001952084,0.00127677,0.006611861,0.00002049774,0.00405877],"category_scores_gemma":[0.005370876,0.0001055516,0.00003967738,0.0008304591,0.00005947145,0.004570723,0.02404754,0.0001141174,0.007458485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008325146,"about_ca_system_score_gemma":0.00004776486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002078071,"about_ca_topic_score_gemma":0.003702225,"domain_scores_codex":[0.995469,0.0002339788,0.0006709461,0.001052129,0.002292343,0.000281616],"domain_scores_gemma":[0.9941429,0.001845695,0.0003059614,0.003515343,0.00005974336,0.0001303762],"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":[0.00003129522,0.00005821013,0.0006600244,0.000004398725,0.00004546076,0.00003715141,0.0003181666,0.00003132007,0.00009679126,0.01602202,0.8722847,0.1104104],"study_design_scores_gemma":[0.0002013256,0.00002408197,0.002267327,0.00002055363,0.00001336622,0.000001375518,0.01450691,0.00407962,0.0002589432,0.004868835,0.9735925,0.0001651509],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03258066,0.00007834277,0.06965495,0.02942528,0.002922221,0.001943266,0.01064454,0.0005180056,0.8522328],"genre_scores_gemma":[0.7185138,0.0002402936,0.01422822,0.008730786,0.0002770257,0.0000849451,0.004919343,0.00004591892,0.2529597],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6859331,"threshold_uncertainty_score":0.99976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5390147190723072,"score_gpt":0.5428906721109037,"score_spread":0.003875953038596447,"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."}}