{"id":"W3159555583","doi":"10.3390/s21093098","title":"Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; University of Saskatchewan","keywords":"Shrub; Grassland; Vegetation (pathology); Remote sensing; Environmental science; Transect; Grassland ecosystem; Growing season; Ecosystem; Agroforestry; Ecology; Geography; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008807707,0.0000472113,0.00005761699,0.000007857488,0.00004484711,0.00001524417,0.00004361907,0.00003778288,0.00001385071],"category_scores_gemma":[0.00009646102,0.00003276644,0.00002915043,0.0001649161,0.00006697023,0.00005175219,0.00002755478,0.0000478764,0.000006841214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004917851,"about_ca_system_score_gemma":0.000005004528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002791012,"about_ca_topic_score_gemma":0.0001055179,"domain_scores_codex":[0.9995236,0.00003359217,0.0001107175,0.0001371899,0.0001124885,0.00008240101],"domain_scores_gemma":[0.9997544,0.00003531855,0.00005866888,0.0001265576,0.000008561114,0.00001651042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00003038136,0.0001002739,0.04910069,0.00003416228,0.00001514875,0.000006440631,0.002115031,0.4901155,0.4488169,0.001156955,0.005800174,0.002708364],"study_design_scores_gemma":[0.000229767,0.00001198527,0.692589,0.00002085641,0.00001451648,0.00002705261,0.0001782415,0.2030696,0.1023099,0.001015943,0.0004545295,0.00007861533],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973599,0.00001016173,0.0009028108,0.0009362788,0.00007010122,0.0001405974,0.000004652284,0.00000627816,0.0005691765],"genre_scores_gemma":[0.9960652,0.000007279333,0.002547815,0.00001994265,0.00001047723,6.792067e-7,0.000006579626,0.000003770328,0.001338287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6434883,"threshold_uncertainty_score":0.1336177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006939480324472521,"score_gpt":0.2212821153205608,"score_spread":0.2143426349960882,"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."}}