{"id":"W6907757661","doi":"10.25318/3410023201-eng","title":"Information system(s) usage for management of publicly owned wastewater assets, Infrastructure Canada, inactive","year":2019,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wastewater; Information system; Key (lock); Information management; Information technology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008409102,0.001696952,0.001468781,0.008215698,0.001702378,0.003422767,0.002551855,0.0009678878,0.06607287],"category_scores_gemma":[0.01016132,0.0008208191,0.001079434,0.03400755,0.0006073218,0.001909789,0.001661762,0.00190218,0.03012226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02026625,"about_ca_system_score_gemma":0.05848652,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9744733,"about_ca_topic_score_gemma":0.9781527,"domain_scores_codex":[0.9975036,0.0001152751,0.000274891,0.0003485049,0.001149158,0.0006086244],"domain_scores_gemma":[0.9864491,0.0008595328,0.000922473,0.000593496,0.01038213,0.000793296],"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":[0.00001941299,0.00000626949,0.001769672,0.000284479,0.00001498684,0.000007691056,0.0000197615,0.0001241003,0.00001282358,0.0003656908,0.995882,0.001493147],"study_design_scores_gemma":[0.0001034477,0.00001017294,0.03374739,0.0006466631,0.00004576633,0.00002989622,0.0003441272,0.0003695896,0.0002355708,0.0004301582,0.9639896,0.00004757634],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009908415,0.00003410572,0.00001548501,0.00004813091,0.00001176725,0.000008796911,0.9983655,0.00004096095,0.001376265],"genre_scores_gemma":[0.0013489,0.000171221,0.0001354747,0.00005274916,0.000008820886,0.00005886817,0.9938748,0.00003958483,0.004309554],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06607287,"threshold_uncertainty_score":0.2210358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004998073546986921,"score_gpt":0.2356945288157206,"score_spread":0.2306964552687337,"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."}}