{"id":"W3173426213","doi":"10.3390/environments8070060","title":"Seasonal Spectral Separation of Western Snowberry and Wolfwillow in Grasslands with Field Spectroradiometer and Simulated Multispectral Bands","year":2021,"lang":"en","type":"article","venue":"Environments","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multispectral image; Spectroradiometer; Hyperspectral imaging; Remote sensing; Grassland; Environmental science; Spectral bands; Broadband; Shrubland; Geography; Ecology; Reflectivity; Ecosystem; Physics; Biology; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002767818,0.000223743,0.0001532616,0.0004483152,0.0002131869,0.0002900311,0.0001411371,0.0002522339,0.0003381092],"category_scores_gemma":[0.0002987549,0.00008869881,0.0002529185,0.0002884876,0.000152471,0.0002740943,0.0001032172,0.0001108327,0.00007399032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002629223,"about_ca_system_score_gemma":0.0001348208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01059726,"about_ca_topic_score_gemma":0.01868492,"domain_scores_codex":[0.9999359,0.00001232983,0.000003122652,0.00001933058,0.00001355575,0.00001577963],"domain_scores_gemma":[0.9998397,0.00005628695,0.00002441726,0.0000112551,0.00004834811,0.00001998527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003020603,0.00134595,0.5025295,0.0002422025,0.0003081027,0.0006656833,0.0007946341,0.1585782,0.2433926,0.0004307646,0.001561248,0.0871305],"study_design_scores_gemma":[0.00003774142,0.000234696,0.7248507,0.00001458685,0.00005178702,0.0001266358,0.0003502528,0.2611541,0.01261369,0.0001611796,0.0003810361,0.00002354529],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992135,0.0000184596,0.0005105137,0.000006797663,0.000001760227,0.000002853966,0.00005120301,0.00002138669,0.0001734549],"genre_scores_gemma":[0.9988576,0.00001239981,0.0008383121,0.000005594019,0.000001172688,0.000003051576,0.0001866442,0.000004720737,0.0000904493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01059726,"threshold_uncertainty_score":0.02107114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003807506168445059,"score_gpt":0.2113443543366728,"score_spread":0.2075368481682278,"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."}}