{"id":"W2885984322","doi":"10.1038/s41598-018-30167-5","title":"Immuno-impedimetric Biosensor for Onsite Monitoring of Ascospores and Forecasting of Sclerotinia Stem Rot of Canola","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Plant pathogens and resistance mechanisms","field":"Agricultural and Biological Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"Alberta Canola Producers Commission; Innotech Alberta; University of Alberta; Alberta Crop Industry Development Fund","keywords":"Sclerotinia sclerotiorum; Sclerotinia; Stem rot; Canola; Biology; Ascocarp; Agronomy; Botany","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":[0.001093952,0.00009129209,0.0002615181,0.00006133509,0.000185881,0.00002931893,0.00009824053,0.00005789122,0.000009436403],"category_scores_gemma":[0.00015551,0.0000383331,0.00008639244,0.0005974073,0.0002335476,0.00006121227,0.00005606139,0.00002921299,2.079474e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007100847,"about_ca_system_score_gemma":0.00001813526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008806164,"about_ca_topic_score_gemma":0.00008889349,"domain_scores_codex":[0.9986249,0.00002190137,0.000553216,0.0003230512,0.0002792553,0.0001976759],"domain_scores_gemma":[0.9986153,0.0001532251,0.0007011584,0.0001133242,0.0003661878,0.00005081599],"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":[0.00002050077,0.00002431341,0.02654667,0.0000441734,0.000009684073,0.000004162118,0.00005961838,0.00000120035,0.9580202,0.00002958174,0.00002987954,0.01521003],"study_design_scores_gemma":[0.0000600001,0.0002072747,0.07714923,0.000139481,0.00001534632,0.00002391383,0.0003305667,0.00004253794,0.9212406,0.0003451883,0.0003627988,0.000083067],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978519,0.000316142,0.000009621053,0.000007830104,0.001378702,0.0002664484,0.00006276065,0.000009602066,0.00009696516],"genre_scores_gemma":[0.9982531,0.00001009804,0.001325056,7.624843e-7,0.00008715859,0.000004567324,0.000009092023,0.000001054469,0.0003090886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05060256,"threshold_uncertainty_score":0.1563179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04226715102715488,"score_gpt":0.2254122614195479,"score_spread":0.183145110392393,"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."}}