{"id":"W2575811143","doi":"10.1007/978-3-319-50100-0_10","title":"Land for Industry in a Multi-industry Ribbon Town","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; The Scarborough Hospital","funders":"","keywords":"Economic rent; Production (economics); Point (geometry); Competition (biology); Business; Economics; Agricultural economics; Industrial organization; Market economy; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001714674,0.0002444285,0.0002576676,0.0004545856,0.007506253,0.004340661,0.0009120743,0.0009576055,0.01652694],"category_scores_gemma":[0.0002649412,0.0001474236,0.0001430689,0.001401403,0.003467671,0.00176434,0.002299829,0.001433895,0.001604084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002808503,"about_ca_system_score_gemma":0.002074542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02077724,"about_ca_topic_score_gemma":0.1571141,"domain_scores_codex":[0.9998053,0.00007615784,0.000003905155,0.00002924331,0.00002500993,0.00006032889],"domain_scores_gemma":[0.999928,0.00001691008,0.000005326267,0.000005426389,0.000007843791,0.00003638947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00009431959,0.0002108111,0.004860387,0.000150004,0.00001361081,0.005074045,0.05460127,0.0008344224,0.001122941,0.7866604,0.05148372,0.0948941],"study_design_scores_gemma":[0.000013994,0.00006982257,0.01090839,0.0002394578,0.00001075611,0.001039976,0.1037271,0.0007858583,0.0004658255,0.05812008,0.8245963,0.00002242865],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1861106,0.00772111,0.001256994,0.00793389,0.0005791984,0.00004263487,0.00009660867,0.0000292764,0.7962297],"genre_scores_gemma":[0.5935135,0.003501021,0.001195582,0.0005121577,0.0001456203,0.00002539162,0.00006928849,0.00004616331,0.4009913],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02077724,"threshold_uncertainty_score":0.05528814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1100635006081921,"score_gpt":0.3469730443986128,"score_spread":0.2369095437904207,"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."}}