{"id":"W4393436843","doi":"10.5281/zenodo.3866267","title":"Best practice templates for tephra collection, analysis, and correlation","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Tephra; Template; Computer science; Geology; Paleontology; Volcano; Programming language","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":[0.007949609,0.002546902,0.00124867,0.005480174,0.001043047,0.003576919,0.003646703,0.002470752,0.02610316],"category_scores_gemma":[0.03393304,0.001358037,0.001932712,0.00715709,0.0008204944,0.003484779,0.004479862,0.002688682,0.0597497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001992419,"about_ca_system_score_gemma":0.004574991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01318485,"about_ca_topic_score_gemma":0.02941015,"domain_scores_codex":[0.9935694,0.00151144,0.001706765,0.001621053,0.001182401,0.0004089967],"domain_scores_gemma":[0.9815812,0.003990119,0.001083453,0.008796763,0.003865557,0.0006829679],"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":[0.0002272808,0.00008176928,0.002705003,0.001125517,0.00006677525,0.0001144709,0.0002164922,0.001927825,0.001691771,0.003762567,0.9551961,0.0328843],"study_design_scores_gemma":[0.0002663289,0.00003272094,0.003717738,0.0003266353,0.00003141849,0.000168006,0.0001897109,0.007439365,0.003920068,0.008411684,0.9754204,0.00007579387],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001572524,0.0002934051,0.04305368,0.0006817415,0.0002481913,0.0008167563,0.9023378,0.04584837,0.005147506],"genre_scores_gemma":[0.002423186,0.0001600531,0.03937523,0.0001731012,0.00003026242,0.002000673,0.952199,0.00231087,0.001327606],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02610316,"threshold_uncertainty_score":0.08732378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02894917673138177,"score_gpt":0.2610586893079527,"score_spread":0.2321095125765709,"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."}}