{"id":"W6986888636","doi":"","title":"Reshaping Toronto's Waterfront","year":2023,"lang":"en","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Water Resources and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Work (physics); Government (linguistics); Natural (archaeology); Face (sociological concept); Perspective (graphical)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002945596,0.0001255184,0.0001433608,0.00140053,0.0005801551,0.0000842149,0.0004853546,0.00009760338,0.0001637408],"category_scores_gemma":[0.00004575056,0.0001293667,0.00009888825,0.003588725,0.0001442256,0.0005510602,0.0001942438,0.0001020691,0.0002012398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004685358,"about_ca_system_score_gemma":0.0002069757,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7422042,"about_ca_topic_score_gemma":0.5021964,"domain_scores_codex":[0.99856,0.0001499574,0.00009919066,0.0003114763,0.0003445691,0.0005348749],"domain_scores_gemma":[0.9995009,0.00004604658,0.0000698748,0.0002211558,0.00005748398,0.000104581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000408488,0.0003017573,0.008220287,0.0001462473,0.0002887926,0.001785992,0.7068772,0.0001669564,0.0001056267,0.08666808,0.04687267,0.1481579],"study_design_scores_gemma":[0.0002955656,0.00003260986,0.0004017252,0.00002830991,0.00001423586,5.588835e-7,0.00732469,0.00006081622,0.00009327472,0.000002876809,0.9915599,0.0001854301],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1132135,0.00000410543,0.00004863988,0.000908925,0.0002743974,0.0002832768,0.00001755624,0.0004988802,0.8847507],"genre_scores_gemma":[0.8499015,0.1426368,0.0002427315,0.0002869501,0.000581113,0.00000368724,0.00002008534,0.00003962887,0.006287534],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9446872,"threshold_uncertainty_score":0.5275421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03199111049936877,"score_gpt":0.257356158481695,"score_spread":0.2253650479823262,"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."}}