{"id":"W4389977755","doi":"10.3390/ijms25010014","title":"Challenges to Cannabis sativa Production from Pathogens and Microbes—The Role of Molecular Diagnostics and Bioinformatics","year":2023,"lang":"en","type":"article","venue":"International Journal of Molecular Sciences","topic":"Plant Virus Research Studies","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Cannabis sativa; Biotechnology; Multiplex; Cannabis; Multiplex polymerase chain reaction; Genomics; Computational biology; Polymerase chain reaction; Genome; Bioinformatics; Genetics; Gene; Botany; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004237396,0.0005736453,0.001207584,0.001841675,0.0009828475,0.005046003,0.001796803,0.001677015,0.002461151],"category_scores_gemma":[0.006842582,0.000453531,0.0007187952,0.001497095,0.001060417,0.002664048,0.001808264,0.002510078,0.001926655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002142173,"about_ca_system_score_gemma":0.004231304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007585831,"about_ca_topic_score_gemma":0.009787642,"domain_scores_codex":[0.9974622,0.0007512422,0.000171605,0.0004095323,0.000972233,0.0002332682],"domain_scores_gemma":[0.9909271,0.003775456,0.001075718,0.0006121203,0.002866315,0.0007433306],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006073482,0.0001981407,0.022216,0.004549067,0.0001462913,0.001019341,0.000817847,0.01269927,0.2144922,0.01933224,0.0266681,0.6972542],"study_design_scores_gemma":[0.00005684705,0.000685584,0.03596181,0.003135036,0.0002475549,0.002306869,0.006308865,0.07623499,0.140016,0.07928635,0.6553473,0.0004127604],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1920136,0.2300809,0.3284633,0.1828244,0.003092943,0.0009428348,0.009453737,0.008887948,0.04424035],"genre_scores_gemma":[0.401099,0.1499047,0.4152571,0.01001976,0.001278216,0.0006233606,0.01118493,0.000779362,0.009853551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007585831,"threshold_uncertainty_score":0.0224098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02806515698968781,"score_gpt":0.2712395174019231,"score_spread":0.2431743604122353,"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."}}