{"id":"W3082810626","doi":"10.1039/d0lc00426j","title":"Single ascospore detection for the forecasting of <i>Sclerotinia</i> stem rot of canola","year":2020,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Plant pathogens and resistance mechanisms","field":"Agricultural and Biological Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Hospital Edmonton; University of Alberta","funders":"Alberta Innovates; Mitacs; Canola Council of Canada","keywords":"Ascospore; Canola; Sclerotinia; Stem rot; Productivity; Agriculture; Sclerotinia sclerotiorum; Sustainability; Engineering; Agricultural engineering; Agronomy; Horticulture; Biology; Botany; Economics; Ecology","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":[0.0001087324,0.00006243906,0.0001155792,0.000002797945,0.00008479162,0.00000789871,0.0001158639,0.00003893257,0.00001180526],"category_scores_gemma":[0.00003189269,0.00001904636,0.00007372107,0.0001404831,0.00001684645,0.0000161213,0.00001622397,0.00004353546,7.939427e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004773039,"about_ca_system_score_gemma":0.000002948666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002469433,"about_ca_topic_score_gemma":0.0005031471,"domain_scores_codex":[0.9995152,0.00001928686,0.0001405127,0.0001155318,0.0001031649,0.0001063358],"domain_scores_gemma":[0.9995944,0.000185284,0.0001279328,0.00002742293,0.00003457006,0.00003040339],"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":[0.00008756971,0.00002135647,0.0001000878,0.00001771841,0.000005846772,4.166434e-7,0.00005778613,0.00002265319,0.9369459,0.0002138841,0.0000227813,0.062504],"study_design_scores_gemma":[0.0001597889,0.0009529619,0.003624569,0.00005116485,0.00001527604,0.000001883097,0.00040057,0.001461654,0.9885153,0.000109577,0.004628738,0.00007853266],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985613,0.00006796882,0.0001112658,0.0005213428,0.00006877808,0.000243729,0.0001651436,0.00001531856,0.0002451921],"genre_scores_gemma":[0.9995853,0.000006482469,0.00006616523,0.0001783047,0.0001069966,0.00001008828,0.000006745719,7.624467e-7,0.00003911866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06242547,"threshold_uncertainty_score":0.07766879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06669827907110572,"score_gpt":0.196388001514804,"score_spread":0.1296897224436983,"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."}}