{"id":"W4407225179","doi":"10.71265/aa9cwm40","title":"The Datafication of Wastewater:","year":2022,"lang":"en","type":"article","venue":"Technology and Regulation","topic":"Water Governance and Infrastructure","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Ottawa","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Government of Canada; Canadian Institutes of Health Research; University of Ottawa","keywords":"Wastewater; Environmental science; Environmental 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.1042745,0.0005213405,0.001046755,0.004848993,0.0106745,0.02949474,0.004077733,0.007705219,0.003216373],"category_scores_gemma":[0.1316689,0.000931964,0.001600097,0.01088735,0.06151882,0.03635032,0.02759935,0.0136805,0.000910648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01210288,"about_ca_system_score_gemma":0.0236341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01005902,"about_ca_topic_score_gemma":0.008496817,"domain_scores_codex":[0.8739939,0.0593995,0.009450045,0.01578427,0.03771056,0.003661616],"domain_scores_gemma":[0.8080043,0.1239994,0.01445921,0.02968066,0.02031278,0.00354364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004383296,0.00003222446,0.006501363,0.0005045395,0.00003094401,0.0002776735,0.02387549,0.0003760496,0.0009133888,0.9037129,0.01243043,0.0513013],"study_design_scores_gemma":[0.00001605029,0.00006221576,0.004957963,0.002252711,0.00002647604,0.0005770176,0.02883821,0.0009359304,0.003187367,0.3803036,0.5787314,0.0001110182],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.08003535,0.01535054,0.2712159,0.4646195,0.00383075,0.0006239483,0.001308477,0.0004239311,0.1625917],"genre_scores_gemma":[0.7791643,0.01327812,0.09939393,0.07781084,0.00249311,0.001224154,0.002089701,0.00059146,0.02395444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9893255,"threshold_uncertainty_score":0.5514629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006087747612167042,"score_gpt":0.2376506534905605,"score_spread":0.2315629058783934,"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."}}