{"id":"W3203742996","doi":"10.18280/ts.380412","title":"SVM Prediction Model Interface for Plant Contaminates","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Leaf Properties and Growth Measurement","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pollution; RGB color model; Air pollution; Support vector machine; Interface (matter); Ocimum; Environmental science; Computer science; Azadirachta; Texture (cosmology); Atmosphere (unit); Mathematics; Artificial intelligence; Image (mathematics); Geography; Horticulture; Meteorology; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001847948,0.00009676127,0.0001057858,0.000003910225,0.000140639,0.00005205686,0.00009191325,0.00004059674,0.0004043189],"category_scores_gemma":[0.00001170086,0.00003637457,0.00007384414,0.00005096151,0.00001680943,0.00007812028,0.00002909814,0.00004585629,0.000008172417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003404011,"about_ca_system_score_gemma":0.00001068886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001812797,"about_ca_topic_score_gemma":0.0000817914,"domain_scores_codex":[0.9992061,0.00002649541,0.0001807295,0.0002136813,0.0001763717,0.0001966615],"domain_scores_gemma":[0.9997379,0.00004079359,0.00003771478,0.0000274118,0.0000992233,0.000057012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001416341,0.0002177327,0.001006935,0.00002538388,0.00004268485,0.000002533915,0.0002313252,0.0006564768,0.9480972,0.000479187,0.008087981,0.04101097],"study_design_scores_gemma":[0.001861414,0.001803573,0.01748068,0.0001474934,0.0001076772,0.00001861562,0.001514922,0.1755162,0.6296428,0.001455644,0.1698778,0.0005732037],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923476,0.0004118478,0.002971976,0.002808127,0.0001848531,0.0003754841,0.0003228324,0.00006793641,0.0005093256],"genre_scores_gemma":[0.9983618,0.00002280374,0.0001993717,0.0003653202,0.0002359498,0.00006927605,0.0001642871,8.95035e-7,0.000580254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3184544,"threshold_uncertainty_score":0.4427009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04411811278862929,"score_gpt":0.2126160328462095,"score_spread":0.1684979200575802,"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."}}