{"id":"W6948616277","doi":"10.5061/dryad.t4b8gtj19","title":"Divergence in life history and behaviour between hybridizing Phymata","year":2021,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Parapatric speciation; Divergence (linguistics); Life history theory; Life history; Gene flow; Natural selection; Juvenile; Vertebrate","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":[0.001317832,0.0007999109,0.0009341425,0.002030629,0.0006909898,0.001016816,0.001744198,0.001104069,0.01328341],"category_scores_gemma":[0.004295785,0.0003316022,0.000767887,0.00303813,0.0003424686,0.0005999468,0.0009953276,0.001202222,0.009744282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007692471,"about_ca_system_score_gemma":0.0007344836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01539741,"about_ca_topic_score_gemma":0.03478032,"domain_scores_codex":[0.999375,0.00009624652,0.0001048009,0.0001846033,0.00009651399,0.0001428045],"domain_scores_gemma":[0.9983852,0.0005255743,0.0003045615,0.0003167452,0.0003115441,0.0001563202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001522935,0.0003869187,0.1652047,0.003390175,0.0004535214,0.0005331544,0.0005970988,0.002071146,0.004009835,0.002356098,0.7960074,0.02346693],"study_design_scores_gemma":[0.0008361191,0.0002245157,0.4694756,0.0007643768,0.0002128632,0.001105728,0.001005652,0.002668555,0.002282899,0.002740287,0.5185617,0.0001216208],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01454219,0.0001096035,0.0002398866,0.00011903,0.00002928552,0.00004361919,0.983878,0.0001036441,0.0009347762],"genre_scores_gemma":[0.01109006,0.00005593225,0.0008165872,0.00006984067,0.000007655841,0.0002366046,0.9870319,0.00002741061,0.0006639326],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01539741,"threshold_uncertainty_score":0.04443741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08198395331410434,"score_gpt":0.2966474036056709,"score_spread":0.2146634502915666,"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."}}