{"id":"W4241952288","doi":"10.1063/1.5001459.15","title":"10.1063/1.5001459.15","year":2017,"lang":"en","type":"dataset","venue":"Default Digital Object Group","topic":"Nonlinear Dynamics and Pattern Formation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Spiral wave; False positive paradox; Core (optical fiber); Collision; Spiral (railway); Computer science; Artificial intelligence; Engineering; Computer security; Telecommunications; Mechanical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002152546,0.0004878284,0.0004527393,0.0002495729,0.0002814515,0.00350409,0.003252215,0.0003685543,0.0002294067],"category_scores_gemma":[0.0001160178,0.0004515249,0.000273023,0.0001671256,0.00007596234,0.00237379,0.001049512,0.0004684681,0.01750058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008865527,"about_ca_system_score_gemma":0.0001045702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001001681,"about_ca_topic_score_gemma":0.0001344675,"domain_scores_codex":[0.9976465,0.00003075011,0.0004725262,0.0006869028,0.0006386612,0.0005247095],"domain_scores_gemma":[0.9967004,0.00008230662,0.0005298104,0.002387188,0.0001138046,0.0001864772],"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":[0.000007454873,0.00008366961,0.000007597076,0.00007177712,0.00003038442,0.00007090273,0.00001352759,0.000002975782,6.952129e-7,0.00008164693,0.9751069,0.0245225],"study_design_scores_gemma":[0.0002724993,0.0001815789,0.00008570636,0.00009373547,0.00001589283,0.00007046293,0.000001659527,0.003654405,0.000002491061,0.000524496,0.9945318,0.0005653086],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004391754,0.00008566996,0.007727079,0.00006831191,0.00105026,0.0002572495,0.9829742,0.000163634,0.007629698],"genre_scores_gemma":[0.000563899,0.00002765329,0.0003694791,0.0001861015,0.000446179,0.00002311934,0.9942666,0.00002761023,0.004089418],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02395719,"threshold_uncertainty_score":0.9997936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01151192100752893,"score_gpt":0.2585269663878103,"score_spread":0.2470150453802813,"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."}}