{"id":"W3111133073","doi":"","title":"Advanced Candidate Crop Analysis Capabilities at the University of Guelph's Controlled Environment Systems Research Facility","year":2018,"lang":"en","type":"article","venue":"42nd COSPAR Scientific Assembly","topic":"Seedling growth and survival studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Environmental science; Computer science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["sts","insufficient_payload"],"category_scores_codex":[0.003840202,0.000166164,0.0004405422,0.0000950105,0.002326126,0.00009582909,0.0006510561,0.00005998016,0.001655228],"category_scores_gemma":[0.0001479508,0.0001183493,0.0001971046,0.001086204,0.004397543,0.0001342153,0.0007280226,0.0001334931,0.001331518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004771164,"about_ca_system_score_gemma":0.00003132672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006309887,"about_ca_topic_score_gemma":0.0075474,"domain_scores_codex":[0.996658,0.0005421197,0.0003052548,0.0007091642,0.001217337,0.0005681174],"domain_scores_gemma":[0.9983354,0.0003805643,0.0001526333,0.0009055377,0.00008045204,0.0001454015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003187956,0.0008195954,0.7415917,0.0001087549,0.00226132,0.00003054733,0.0258576,0.04466482,0.1190313,0.0005840595,0.05362168,0.008240665],"study_design_scores_gemma":[0.004441456,0.0005257622,0.5528366,0.00003212861,0.0007770753,0.000003184027,0.02057219,0.02431245,0.009821447,0.000352378,0.3854424,0.0008829011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985409,0.0003601799,0.0005668378,0.0002363512,0.0004029495,0.0005571807,0.0001030021,0.00002389401,0.01234062],"genre_scores_gemma":[0.9753196,0.00003629784,0.00006032259,0.000007889329,0.00001799747,0.000009885721,0.00001585967,0.000004696643,0.02452744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3318208,"threshold_uncertainty_score":0.999446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0247545911715617,"score_gpt":0.2538101856426665,"score_spread":0.2290555944711048,"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."}}