{"id":"W2981642257","doi":"10.4095/219795","title":"Estimation of Crop Cover and Chlorophyll from Hyperspectral Remote Sensing","year":2001,"lang":"en","type":"report","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Hyperspectral imaging; Remote sensing; Cover (algebra); Estimation; Crop; Environmental science; Chlorophyll; Cover crop; Geography; Biology; Agroforestry; Forestry; Botany; Engineering","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":[0.000141911,0.000336629,0.000178143,0.0008311903,0.0001641296,0.0002787675,0.0001693717,0.000155515,0.0005814723],"category_scores_gemma":[0.0004692466,0.0001710024,0.0001615802,0.0006830739,0.0001491691,0.0002944744,0.0001874021,0.0001278551,0.0002902414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005449267,"about_ca_system_score_gemma":0.0003459014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0407003,"about_ca_topic_score_gemma":0.09657082,"domain_scores_codex":[0.9998902,0.00001081406,0.000002484752,0.0000240797,0.00005871921,0.0000135799],"domain_scores_gemma":[0.9999171,0.00001701983,0.00001886462,0.000008768947,0.00003196128,0.000006308078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003839425,0.0001232161,0.2420101,0.0002655765,0.0001646204,0.0002242028,0.0002817029,0.05432262,0.4327671,0.0004837785,0.001349681,0.2676234],"study_design_scores_gemma":[0.00002865787,0.00007927465,0.7812449,0.00001385961,0.0000535828,0.000161263,0.0001659276,0.1590516,0.05654492,0.0005583382,0.002058466,0.00003927551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747898,0.0002564401,0.02183656,0.00002516508,0.000002610705,0.00003586098,0.0007742457,0.0001548901,0.002124408],"genre_scores_gemma":[0.9695458,0.0002758214,0.02722169,0.00001191054,0.000003819451,0.00002379096,0.00190389,0.0000269077,0.0009864728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0407003,"threshold_uncertainty_score":0.08092678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02468746234124715,"score_gpt":0.2430002067319242,"score_spread":0.218312744390677,"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."}}