{"id":"W4200154574","doi":"10.4018/978-1-7998-8482-8.ch033","title":"Mapping Plastic Greenhouses With LANDSAT 8 Imagery in Valparaiso, Chile","year":2021,"lang":"en","type":"book-chapter","venue":"Practice, progress, and proficiency in sustainability","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Subsidy; Greenhouse; Geography; Agriculture; Census; Government (linguistics); Intersection (aeronautics); Food security; Cartography; Agricultural economics; Physical geography; Political science; Horticulture; Archaeology; Economics; Demography; Biology","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":[0.0002018371,0.0003159684,0.0001060518,0.001031216,0.0002021317,0.0007860561,0.0003035265,0.0002036839,0.001348105],"category_scores_gemma":[0.0003374907,0.0001500253,0.0002100611,0.001192311,0.0001870529,0.0005612823,0.0003709858,0.0001320566,0.00034329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007044493,"about_ca_system_score_gemma":0.0005031825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07768594,"about_ca_topic_score_gemma":0.1275041,"domain_scores_codex":[0.9999349,0.000009924574,0.000003617276,0.00002419041,0.0000157694,0.00001171459],"domain_scores_gemma":[0.9999331,0.00002048442,0.00001010529,0.000006400471,0.00002389207,0.000006026601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003918219,0.0003029091,0.3525523,0.00135644,0.0002353714,0.003257963,0.005049411,0.05196184,0.05726061,0.002135573,0.02160289,0.503893],"study_design_scores_gemma":[0.00004812277,0.00008514445,0.8884022,0.0002329266,0.00007615242,0.0004546387,0.008014333,0.05434646,0.00805716,0.0008732559,0.03933201,0.00007764744],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670426,0.001567836,0.00388348,0.0002671549,0.00002946973,0.00007409984,0.004313101,0.0004053602,0.02241683],"genre_scores_gemma":[0.9760044,0.001135279,0.007422181,0.00004780207,0.00001551629,0.00006624058,0.005519398,0.00006522581,0.009724054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07768594,"threshold_uncertainty_score":0.1544675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009144161718034689,"score_gpt":0.2420923533543514,"score_spread":0.2329481916363167,"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."}}