{"id":"W6929935516","doi":"10.5061/dryad.384nf","title":"Data from: Estimating uncertainty in multivariate responses to selection","year":2013,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Cancer-related Molecular Pathways","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Selection (genetic algorithm); Multivariate statistics; Natural selection; Covariance; Multivariate analysis; Realization (probability)","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":[0.002865555,0.001502298,0.001322053,0.002553295,0.0007163863,0.001963234,0.003770565,0.002325541,0.01788241],"category_scores_gemma":[0.015264,0.0006255336,0.001801976,0.004436953,0.0005933939,0.0009624279,0.00215503,0.001810009,0.01329856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001876204,"about_ca_system_score_gemma":0.002876464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02343936,"about_ca_topic_score_gemma":0.04805269,"domain_scores_codex":[0.9985386,0.0004007733,0.0002079,0.0003780026,0.0003296058,0.0001450157],"domain_scores_gemma":[0.9961309,0.001779801,0.0004403692,0.0009027499,0.0004972362,0.000249024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005938403,0.0000929889,0.01821171,0.003200501,0.0005091736,0.000191158,0.0001347833,0.006057925,0.0006440505,0.00403399,0.9501188,0.01621106],"study_design_scores_gemma":[0.001124552,0.00006252656,0.03417115,0.0006362792,0.0002610609,0.0003753469,0.000156301,0.008077029,0.002116529,0.01239575,0.9404971,0.0001263736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001323475,0.0002638697,0.0007972316,0.0002936671,0.00003282797,0.00003717939,0.9957963,0.0007827992,0.0006726517],"genre_scores_gemma":[0.004691869,0.000198654,0.003026611,0.0001671702,0.00001330508,0.0002736567,0.9910047,0.0001094692,0.0005144182],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02343936,"threshold_uncertainty_score":0.05982262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04855810251367271,"score_gpt":0.3227038229688281,"score_spread":0.2741457204551554,"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."}}