{"id":"W2936059024","doi":"10.1016/j.ecolmodel.2019.03.002","title":"A spatially-explicit, individual-based demogenetic simulation framework for evaluating hybridization dynamics","year":2019,"lang":"en","type":"article","venue":"Ecological Modelling","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Forest Service; Canada Research Chairs; Natural Resources Canada; University of Toronto","funders":"City, University of London; National Aeronautics and Space Administration","keywords":"Sympatric speciation; Salvelinus; Ecology; Trout; Selection (genetic algorithm); Temporal scales; Biology; Computer science; Machine learning; Fish <Actinopterygii>; Fishery","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":[0.001389963,0.0004439417,0.0007409387,0.0008401489,0.0007541745,0.001049534,0.002143991,0.001814467,0.00298031],"category_scores_gemma":[0.004744133,0.0005274058,0.0007679035,0.0007537744,0.0009966182,0.001278525,0.001619942,0.0009286087,0.0002640736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001613745,"about_ca_system_score_gemma":0.001667199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03011579,"about_ca_topic_score_gemma":0.02660908,"domain_scores_codex":[0.9996071,0.0002116253,0.00001902645,0.0000567662,0.00005247407,0.00005294604],"domain_scores_gemma":[0.9981502,0.001179225,0.0001908672,0.0001491811,0.000161926,0.0001685504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005861158,0.00001401571,0.0004025153,0.000003582997,0.000009083586,0.00001198137,0.00001452819,0.9941878,0.00009224568,0.004600807,0.00004283686,0.0006147399],"study_design_scores_gemma":[0.000002923672,0.00000423724,0.00007806477,0.000001255868,0.000003165898,0.000004015535,0.000005632956,0.9981724,0.00002069795,0.001614851,0.00009016358,0.000002533448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2899993,0.00022595,0.6950243,0.0007102198,0.00005932617,0.000118377,0.0006229791,0.0003988582,0.01284067],"genre_scores_gemma":[0.9368074,0.0001159587,0.06031599,0.00007465189,0.00002317849,0.0001353492,0.0002025274,0.00005494216,0.002269908],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03011579,"threshold_uncertainty_score":0.05988097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04821126836693343,"score_gpt":0.2954277691465272,"score_spread":0.2472165007795938,"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."}}