{"id":"W7084387776","doi":"10.4230/artifacts.24666","title":"KaMinPar","year":2025,"lang":"en","type":"other","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Bacterial Genetics and Biotechnology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Disjoint sets; Partition (number theory); Speedup; Graph; Graph partition","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004364097,0.001730666,0.0008462552,0.001102986,0.001066396,0.001822833,0.002063956,0.001088212,0.05322435],"category_scores_gemma":[0.002209862,0.0006302843,0.0009094003,0.001092955,0.0005735773,0.002779472,0.002223729,0.001248092,0.02752886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008101619,"about_ca_system_score_gemma":0.0009533755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001375931,"about_ca_topic_score_gemma":0.003615555,"domain_scores_codex":[0.9995975,0.00005321229,0.00001504074,0.0001405339,0.0001161956,0.00007758618],"domain_scores_gemma":[0.9995682,0.0001270772,0.00002785257,0.0001566739,0.0000775757,0.00004257963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008474159,0.0003684138,0.001710837,0.001792488,0.0001826309,0.0002853312,0.000274275,0.04857785,0.03066826,0.1125196,0.3826219,0.420151],"study_design_scores_gemma":[0.0003575692,0.0002426016,0.001102725,0.0001791931,0.00009336815,0.0006627493,0.0002218898,0.3975269,0.04441831,0.1205307,0.4345702,0.0000938836],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02860415,0.001637856,0.5895547,0.001107184,0.0004185533,0.0004778422,0.01085209,0.1630377,0.2043099],"genre_scores_gemma":[0.2070238,0.001552169,0.6193229,0.001114665,0.0001677602,0.0008688553,0.03658593,0.03396115,0.09940281],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05322435,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005440651133032692,"score_gpt":0.2342347921704082,"score_spread":0.2287941410373756,"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."}}