{"id":"W2519775678","doi":"10.1111/eva.12432","title":"Identifying patterns of dispersal, connectivity and selection in the sea scallop,<i>Placopecten magellanicus,</i>using<scp>RAD</scp>seq‐derived<scp>SNP</scp>s","year":2016,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Marine Bivalve and Aquaculture Studies","field":"Environmental Science","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Fisheries and Oceans Canada; Bedford Institute of Oceanography; Memorial University of Newfoundland","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Scallop; Biological dispersal; Selection (genetic algorithm); SNP; Evolutionary biology; Ecology; Genetics; Gene; Single-nucleotide polymorphism; Demography; Genotype","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":[0.0002678194,0.0001245653,0.0001465008,0.000695257,0.0003781062,0.0003924361,0.0001965314,0.0001400135,0.0006653653],"category_scores_gemma":[0.0004395009,0.0001126696,0.0001913922,0.0004622725,0.00033573,0.0001501407,0.0002952835,0.0001873448,0.000102693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003898247,"about_ca_system_score_gemma":0.000285741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03860658,"about_ca_topic_score_gemma":0.1027681,"domain_scores_codex":[0.9998939,0.00001404565,0.00000702055,0.00005395539,0.00001301454,0.00001810918],"domain_scores_gemma":[0.9996995,0.00006741994,0.0001253674,0.00001779691,0.00003688573,0.00005296942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005530545,0.00001189009,0.9763629,0.00001279387,0.00006763389,0.00004884451,0.0002890068,0.000413391,0.01935656,0.00002731463,0.0000655916,0.00328869],"study_design_scores_gemma":[0.000001211359,0.000008569704,0.9991316,0.00000190194,0.000006976381,0.00001844196,0.00009067322,0.000475456,0.0002235477,0.00000677781,0.00003358863,0.000001231731],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997209,0.000008942677,0.0001249099,0.00000464574,1.927454e-7,0.000001074182,0.0000775948,0.000001751089,0.00005992386],"genre_scores_gemma":[0.9995224,0.0000085908,0.000240356,0.000006424034,4.655739e-7,0.000002123091,0.0001600515,0.000001327605,0.00005826998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03860658,"threshold_uncertainty_score":0.07676375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01633331934227999,"score_gpt":0.2530947210284165,"score_spread":0.2367614016861365,"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."}}