{"id":"W4392905964","doi":"10.32920/25417129","title":"Municipal Asset Management Planning in Ontario: An Analysis of Water, Wastewater and Stormwater Asset Management Planning in Selected Ontario Municipalities","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York Central Hospital; York University","funders":"","keywords":"Asset management; Stormwater; Business; Asset (computer security); IT asset management; Environmental planning; Best practice; Environmental resource management; Finance; Environmental science; Economics; Computer science; Surface runoff; Management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001258262,0.0001979931,0.0002811294,0.002191685,0.004606646,0.002219638,0.0009913255,0.0003745393,0.002338943],"category_scores_gemma":[0.006259747,0.0004160427,0.0003381681,0.01056204,0.001404232,0.0007237145,0.001594111,0.0003865139,0.0001759335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07789463,"about_ca_system_score_gemma":0.08498288,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9909893,"about_ca_topic_score_gemma":0.9970087,"domain_scores_codex":[0.9979195,0.0002549322,0.0001440571,0.0001476743,0.0008711253,0.000662671],"domain_scores_gemma":[0.9925098,0.001413926,0.001763773,0.0002732161,0.002882718,0.001156621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001447601,0.00009988221,0.7844931,0.0005232101,0.00008458496,0.001465068,0.1598263,0.001850511,0.001240842,0.00357205,0.005165314,0.04153434],"study_design_scores_gemma":[0.00000516161,0.00002627587,0.8644885,0.0001056089,0.00001767687,0.00005707602,0.1185037,0.0004706017,0.0001091567,0.000107613,0.01609172,0.00001691301],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846187,0.0003624184,0.000268112,0.0006213356,0.000005030533,0.0001604464,0.001427129,0.0000102985,0.01252647],"genre_scores_gemma":[0.9934703,0.0007095181,0.000624078,0.00008400595,0.000003457582,0.00009361009,0.001034049,0.00001149469,0.003969434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07789463,"threshold_uncertainty_score":0.5651677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01737555155896398,"score_gpt":0.249718267464617,"score_spread":0.2323427159056531,"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."}}