{"id":"W4301603063","doi":"10.22541/au.166497092.26503349/v1","title":"NAPPN Annual Conference Abstract: Dissecting lentil crop growth across multi- environment trials using unoccupied aerial vehicles","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Phenomics; Throughput; Proxy (statistics); Population; Biomass (ecology); Computer science; Environmental science; Cartography; Geography; Biology; Ecology; Machine learning; Genomics","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":[0.001865486,0.0005097016,0.0003936067,0.000787416,0.0005168705,0.001561318,0.000782816,0.000554404,0.02243408],"category_scores_gemma":[0.0008814663,0.0001683311,0.0003834051,0.0006020209,0.0003013814,0.0006501005,0.001568003,0.001145017,0.008323517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001063586,"about_ca_system_score_gemma":0.001401125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006317537,"about_ca_topic_score_gemma":0.02021545,"domain_scores_codex":[0.9995079,0.00006653358,0.00001471583,0.00009093664,0.0002781056,0.00004179007],"domain_scores_gemma":[0.9989838,0.00006742889,0.00004673006,0.00009285754,0.0005817874,0.0002274076],"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":[0.0006931652,0.0005177854,0.0149931,0.0006999001,0.0001272455,0.0005104106,0.000406192,0.002335486,0.1000881,0.002105261,0.415306,0.4622173],"study_design_scores_gemma":[0.00008883978,0.0009535478,0.09452756,0.0003334377,0.00006835999,0.0003916718,0.0005861201,0.004026006,0.03152982,0.002513295,0.8648721,0.0001093036],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2742603,0.01754654,0.1409377,0.02001053,0.02690636,0.002981824,0.04903647,0.01162715,0.4566931],"genre_scores_gemma":[0.3567247,0.01460642,0.1027699,0.004847778,0.003926443,0.002362219,0.05346772,0.003537857,0.4577571],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02243408,"threshold_uncertainty_score":0.07504952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1467994066243381,"score_gpt":0.3156992464212378,"score_spread":0.1688998397968997,"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."}}