{"id":"W7152347752","doi":"","title":"Toward an Open Database of Public Land Ownership: A key to addressing housing affordability challenges in Canadian cities","year":2025,"lang":"en","type":"article","venue":"TSpace","topic":"Urban Planning and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Key (lock); Urban planning; Government (linguistics); Land use; Democracy; Public policy","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":[0.0109402,0.0007460343,0.001118397,0.01581694,0.007422367,0.0162387,0.00491733,0.001668296,0.01746397],"category_scores_gemma":[0.05507049,0.0008153613,0.0008518273,0.04227551,0.002631743,0.01119567,0.007574456,0.003205944,0.006132021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03630205,"about_ca_system_score_gemma":0.1154217,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9821137,"about_ca_topic_score_gemma":0.9875073,"domain_scores_codex":[0.990418,0.001046909,0.0006144805,0.0008249284,0.006018525,0.001077132],"domain_scores_gemma":[0.9290985,0.004477833,0.002433007,0.00957913,0.05079161,0.003619856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006614237,0.0001154383,0.04008926,0.0004315377,0.00005528468,0.0001204784,0.005194288,0.003453127,0.0007438675,0.1470369,0.5690889,0.2336048],"study_design_scores_gemma":[0.00001513711,0.00001455048,0.03955169,0.0007940653,0.00003552581,0.00005503006,0.007549137,0.00872087,0.0009951612,0.02496465,0.9171473,0.0001568445],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.04654165,0.006456059,0.1364825,0.09038194,0.001677129,0.001454702,0.4307087,0.006405903,0.2798914],"genre_scores_gemma":[0.2940951,0.01329328,0.2650306,0.006285386,0.0008582248,0.001216294,0.3400917,0.002986492,0.076143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03630205,"threshold_uncertainty_score":0.263391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2845720738413434,"score_gpt":0.4136276026555332,"score_spread":0.1290555288141899,"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."}}