{"id":"W6948095673","doi":"10.4230/dagrep.12.6","title":"Dagstuhl Reports, Volume 12, Issue 6, June 2022, Complete Issue","year":2023,"lang":"en","type":"other","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidade do Porto; Università di Bologna; Universitetet i Bergen; Simon Fraser University; Aalto-Yliopisto; University of Sussex; London School of Economics and Political Science; University College London; University of Toronto; University of Cyprus; Institut national de recherche en informatique et en automatique (INRIA); University of Central Florida; Technische Universiteit Delft; Aarhus Universitet; Sorbonne Université; Microsoft Research","keywords":"Volume (thermodynamics); Term (time); Work (physics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003400794,0.002151062,0.001543287,0.004796107,0.002352022,0.01276812,0.002091873,0.002782216,0.7547961],"category_scores_gemma":[0.01157317,0.0009656837,0.0009752338,0.004563804,0.0007812235,0.003960566,0.003413233,0.003093469,0.8202389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003554451,"about_ca_system_score_gemma":0.006702095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00883487,"about_ca_topic_score_gemma":0.0148662,"domain_scores_codex":[0.9973567,0.0001982701,0.0001460792,0.0002293227,0.00172078,0.0003489302],"domain_scores_gemma":[0.9935867,0.0006153997,0.0002535286,0.0006588293,0.002551137,0.002334426],"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":[0.00001579902,0.00001267885,0.00001909908,0.00003388802,0.000001185603,0.000006857078,0.000002877267,0.00001588806,0.00005617688,0.0005003808,0.9901376,0.009197578],"study_design_scores_gemma":[0.00001322315,0.00000760022,0.0001428195,0.00002195873,0.00000186325,0.000009711268,0.000009622599,0.00003464279,0.0001166171,0.0005306765,0.9991052,0.000006084178],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005905752,0.003678154,0.002315697,0.01594331,0.05835899,0.0004313314,0.05455031,0.009350204,0.8547814],"genre_scores_gemma":[0.000967505,0.0008925233,0.0006287515,0.001143288,0.001425638,0.00009712565,0.01410935,0.001634656,0.9791013],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7547961,"threshold_uncertainty_score":0.3497535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166760916817848,"score_gpt":0.243139897119717,"score_spread":0.2314722879515385,"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."}}