{"id":"W4399650109","doi":"10.32614/cran.package.expm","title":"expm: Matrix Exponential, Log, 'etc'","year":2010,"lang":"en","type":"dataset","venue":"","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Actua","funders":"","keywords":"Matrix exponential; Exponential function; Matrix (chemical analysis); Mathematics; Applied mathematics; Statistics; Mathematical analysis; Chemistry; Chromatography","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":[0.001489763,0.005160855,0.002059662,0.004097666,0.000775128,0.002627673,0.004943408,0.002017569,0.02926206],"category_scores_gemma":[0.00782722,0.001050194,0.002197347,0.006543136,0.0005269781,0.002470347,0.001951787,0.002803503,0.05617949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001579968,"about_ca_system_score_gemma":0.001980904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01093445,"about_ca_topic_score_gemma":0.02316208,"domain_scores_codex":[0.9983589,0.0002209938,0.0002443691,0.0004711312,0.0004871074,0.0002174911],"domain_scores_gemma":[0.9972538,0.0006644995,0.0002646952,0.001108071,0.0005640179,0.000144867],"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":[0.0001225575,0.00005103611,0.0009061355,0.0006595895,0.00004329181,0.00002060123,0.00001189632,0.0007470708,0.0002295577,0.0007053155,0.9889487,0.00755427],"study_design_scores_gemma":[0.0006780837,0.0001006592,0.00616914,0.00022603,0.00006266317,0.000302648,0.00007928864,0.00789967,0.004216021,0.007515383,0.9726404,0.0001100747],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.0009211966,0.000243169,0.001743831,0.0001530271,0.00008936146,0.00005210639,0.9857626,0.009578723,0.001455913],"genre_scores_gemma":[0.001788239,0.0001627018,0.00485832,0.0001216634,0.00003054279,0.000231107,0.9908087,0.0009256363,0.001073126],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02926206,"threshold_uncertainty_score":0.09789139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01078951566487924,"score_gpt":0.2658454697796941,"score_spread":0.2550559541148149,"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."}}