{"id":"W4412713916","doi":"10.69520/jipe.v7i1.261","title":"Clustering Ontario Renters","year":2025,"lang":"en","type":"article","venue":"Journal of innovation in polytechnic education.","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Conestoga College","funders":"","keywords":"Renting; Purchasing; Business; Marketing; Plan (archaeology); Cluster (spacecraft); Geography; Political science; Computer science","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":[0.000577342,0.0003360675,0.0004386289,0.003897289,0.003267851,0.00162737,0.0008807322,0.0003728415,0.007382761],"category_scores_gemma":[0.002968606,0.0002521156,0.0004656683,0.007134235,0.0006073238,0.0003677738,0.001149721,0.0002014631,0.0009486317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02195817,"about_ca_system_score_gemma":0.02330053,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9875595,"about_ca_topic_score_gemma":0.9950346,"domain_scores_codex":[0.9985152,0.00008436798,0.00006739359,0.0002206266,0.0006957123,0.0004167524],"domain_scores_gemma":[0.9981381,0.00007202891,0.0001955793,0.00007998845,0.001287341,0.0002269795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001843217,0.00007128955,0.9083531,0.0002165704,0.00006993089,0.0003817083,0.01853088,0.0008124509,0.002560432,0.001466666,0.02315908,0.04419361],"study_design_scores_gemma":[0.000007901173,0.00002397622,0.9696545,0.00004228748,0.00002030107,0.00006595249,0.01282155,0.001119169,0.0002341526,0.0001121666,0.01587331,0.00002474828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9663454,0.0002917823,0.001142613,0.0002786719,0.00002332564,0.0007970639,0.01192633,0.000042404,0.01915253],"genre_scores_gemma":[0.9660382,0.0004909475,0.003558549,0.000084836,0.000009035651,0.0003737736,0.008067732,0.00002704538,0.02134999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02195817,"threshold_uncertainty_score":0.1593184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02500140477624663,"score_gpt":0.3464851466685551,"score_spread":0.3214837418923084,"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."}}