{"id":"W6929743059","doi":"10.5061/dryad.sc0nf","title":"Data from: Clones or clans: the genetic structure of a deep-sea sponge, Aphrocallistes vastus, in unique sponge reefs of British Columbia, Canada","year":2016,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Reef; Genetic structure; Biological dispersal; Population; Sponge; Trawling; Coral reef","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0007806277,0.0004188562,0.0009809752,0.00008481646,0.000165431,0.0003104333,0.01250199,0.0002640678,0.00004208296],"category_scores_gemma":[0.00005837515,0.0003609135,0.00004540291,0.0004896178,0.0002380962,0.0004572615,0.006216629,0.0006332152,3.800915e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003400144,"about_ca_system_score_gemma":0.0006340496,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9231585,"about_ca_topic_score_gemma":0.9989313,"domain_scores_codex":[0.9952832,0.001048224,0.0009454595,0.001540621,0.0005767303,0.0006057032],"domain_scores_gemma":[0.9910216,0.001637885,0.0006932546,0.006392451,0.00006753903,0.0001872702],"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":[0.0001274222,0.00009180199,0.004105346,0.001729194,0.0003358029,0.0004253063,0.0003691805,0.00003745607,0.00007989621,0.00001674164,0.8927733,0.09990861],"study_design_scores_gemma":[0.001514507,0.0001929084,0.1162082,0.008415055,0.0005214377,0.0003808704,0.0001760644,0.1395504,0.000008788768,0.006143202,0.7249973,0.001891239],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008128535,0.003002289,0.07551935,0.00006566573,0.0003859206,0.0004116097,0.9124553,0.00001965395,0.00001170633],"genre_scores_gemma":[0.003146064,0.006032595,0.06324061,0.0004504721,0.0004714735,0.00001213627,0.926549,0.00004393536,0.00005377406],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1677759,"threshold_uncertainty_score":0.9998843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01754972884278086,"score_gpt":0.244610922070071,"score_spread":0.2270611932272901,"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."}}