{"id":"W6948580058","doi":"10.5061/dryad.3n6qm3p","title":"Data from: Estimating the impact of divergent mating phenology between residents and migrants on the potential for gene flow","year":2019,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Gene flow; Phenology; Mating; Reproductive isolation; Pollen; Divergence (linguistics); Pollination; Genetic divergence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002280193,0.0006562906,0.0007658544,0.001502885,0.0005301597,0.001118146,0.0009054504,0.001029624,0.03591587],"category_scores_gemma":[0.008150835,0.0003937326,0.0005770309,0.001586454,0.0002960784,0.0009233562,0.001046707,0.001073217,0.0238543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005323071,"about_ca_system_score_gemma":0.0008663759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004479513,"about_ca_topic_score_gemma":0.007899646,"domain_scores_codex":[0.9986606,0.0002237065,0.0002133672,0.0003024042,0.0005125275,0.0000874191],"domain_scores_gemma":[0.992994,0.002433559,0.0005993327,0.00169701,0.001951837,0.0003241513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004183527,0.001651021,0.3132159,0.003129873,0.0008113889,0.0005361723,0.001004711,0.008173586,0.0524395,0.002931079,0.3732938,0.2386294],"study_design_scores_gemma":[0.0009531708,0.0008890564,0.529861,0.0003961213,0.0003439498,0.0004067126,0.0004490933,0.01741207,0.0390848,0.002604208,0.4073644,0.0002354821],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1454677,0.0003802457,0.01496785,0.0009956303,0.0003812043,0.001049,0.8089703,0.005074601,0.02271347],"genre_scores_gemma":[0.2016318,0.0002827551,0.03251228,0.0004844316,0.0001095233,0.002845089,0.7453945,0.000895591,0.015844],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03591587,"threshold_uncertainty_score":0.1201506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0726529062485005,"score_gpt":0.3134855432097976,"score_spread":0.2408326369612971,"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."}}