{"id":"W4206582506","doi":"10.3389/fpls.2021.797425","title":"Optimizing Photoperiod Switch to Maximize Floral Biomass and Cannabinoid Yield in Cannabis sativa L.: A Meta-Analytic Quantile Regression Approach","year":2022,"lang":"en","type":"review","venue":"Frontiers in Plant Science","topic":"Plant Parasitism and Resistance","field":"Agricultural and Biological Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cannabis sativa; Yield (engineering); Biomass (ecology); Biology; Quantile regression; photoperiodism; Cannabinoid; Botany; Gynoecium; Agronomy; Mathematics; Statistics; Genetics","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":[0.001487719,0.0005360923,0.002110167,0.000378692,0.0004689849,0.000226927,0.001370708,0.0002028429,0.0001051154],"category_scores_gemma":[0.0001990814,0.000207218,0.000279626,0.003282294,0.0002870775,0.0002840054,0.0004573788,0.0005328365,0.000003195564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003143719,"about_ca_system_score_gemma":0.0002172286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002931217,"about_ca_topic_score_gemma":0.00215894,"domain_scores_codex":[0.9959823,0.0002455841,0.000716321,0.001410226,0.000761134,0.000884475],"domain_scores_gemma":[0.9990422,0.0001261724,0.0003089124,0.0002090235,0.00002065641,0.0002930349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003715746,0.0006653278,0.003396399,0.005355755,0.0006600634,0.001894936,0.002330162,0.0002198109,0.002793179,0.0001402171,0.07475149,0.9074211],"study_design_scores_gemma":[0.0001297343,0.0001188931,0.0008325313,0.001499954,0.0004820404,0.0001954945,0.0008231302,0.0006803563,0.00004424747,0.00002602225,0.9941773,0.0009902607],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004575139,0.9910462,0.00003066139,0.0002612681,0.000742204,0.001308756,0.001261331,0.00003882262,0.0007355796],"genre_scores_gemma":[0.001988932,0.9910834,0.004704372,0.0001376506,0.00007071388,0.0005935236,0.0003250299,0.000006605698,0.001089777],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9194258,"threshold_uncertainty_score":0.8450106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07541204155749096,"score_gpt":0.2793869823887194,"score_spread":0.2039749408312284,"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."}}