{"id":"W2897961079","doi":"10.1080/07038992.2018.1462660","title":"Image-Based Rapid Estimation of Frost Damage in Canola (<i>Brassica napus</i> L.)","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"College of Agriculture and Bioresources, University of Saskatchewan; Global Fund to Fight AIDS, Tuberculosis and Malaria","keywords":"Canola; Brassica; Frost (temperature); Estimation; Geography; Horticulture; Agronomy; Biology; Botany; Engineering; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.000152972,0.0003025681,0.0002355289,0.0008427291,0.0001515474,0.0002769774,0.0002611557,0.0002070215,0.0003851641],"category_scores_gemma":[0.0001732943,0.0001451703,0.0001491138,0.0002865203,0.00009417355,0.0002701949,0.0001607689,0.0002494717,0.0001109494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003174452,"about_ca_system_score_gemma":0.0001077315,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007581165,"about_ca_topic_score_gemma":0.01548757,"domain_scores_codex":[0.9999304,0.000006359917,0.000002529554,0.0000249093,0.00002696331,0.000008888284],"domain_scores_gemma":[0.9999094,0.0000149197,0.0000253917,0.000006343102,0.0000278827,0.00001602778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002988313,0.00009224666,0.0230807,0.0001405806,0.00003568844,0.00006599837,0.00013369,0.001542282,0.9464242,0.00003756628,0.0001425982,0.02800565],"study_design_scores_gemma":[0.00001801267,0.0004201563,0.7565776,0.000015813,0.0001008968,0.0002843084,0.0002545907,0.0266043,0.2145911,0.00008812171,0.0009919548,0.00005308951],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937483,0.0005473037,0.004749782,0.00001333887,0.000004689746,0.00002571604,0.0002879902,0.00009403648,0.0005287673],"genre_scores_gemma":[0.9852219,0.0004507335,0.01288697,0.00001979412,0.000004777654,0.00003634944,0.0007070576,0.00001800575,0.0006544591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9924188,"threshold_uncertainty_score":0.01507407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007010191235486153,"score_gpt":0.2074895703202141,"score_spread":0.2004793790847279,"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."}}