{"id":"W4387126874","doi":"10.1101/2023.09.26.559561","title":"A simple method to genetically differentiate invasive F <sub>1</sub> <i>Typha</i> hybrids ( <i>T</i> . × <i>glauca</i> ) and advanced-generation/backcrossed hybrids from parent species ( <i>T. latifolia</i> and <i>T. angustifolia</i> ) in eastern Canada and northeastern USA","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Universities Space Research Association","keywords":"Hybrid; Biology; Introgression; Taxon; Range (aeronautics); Microsatellite; Typha; Invasive species; Genetic marker; Botany; Wetland; Gene; Genetics; Ecology; Allele","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001464764,0.0003464689,0.0002022199,0.0008541437,0.0002798353,0.0003540507,0.000299233,0.0004787995,0.001783737],"category_scores_gemma":[0.0003481863,0.0002117605,0.0002746041,0.000306187,0.0002406124,0.000184716,0.0002233704,0.0005613182,0.0008239858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000230619,"about_ca_system_score_gemma":0.0003357154,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006954717,"about_ca_topic_score_gemma":0.03207424,"domain_scores_codex":[0.9998435,0.00001127329,0.0000175292,0.00006455393,0.00004423967,0.00001896522],"domain_scores_gemma":[0.999625,0.00005733622,0.0001217809,0.00003824358,0.0001037495,0.00005388582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004218487,0.00003495848,0.01082057,0.00003894018,0.00001314634,0.00006499552,0.00008322874,0.00007552833,0.9760243,0.00007681824,0.0001817418,0.01254351],"study_design_scores_gemma":[0.00004663819,0.0005155422,0.3817731,0.00006903347,0.0001992614,0.001605452,0.0004451794,0.004248821,0.5916675,0.000238569,0.01911894,0.00007191137],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9013701,0.0004384988,0.08866051,0.000157467,0.00007812365,0.0003483141,0.003001562,0.0007934457,0.005152001],"genre_scores_gemma":[0.7268611,0.0003804406,0.2587387,0.000256639,0.00001469885,0.0003410207,0.005455805,0.0001663779,0.007785214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9930453,"threshold_uncertainty_score":0.01382852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01334182738686839,"score_gpt":0.2064806374247403,"score_spread":0.1931388100378719,"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."}}