{"id":"W3122401951","doi":"10.20944/preprints201709.0055.v1","title":"Introduction to Reconfiguration","year":2017,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Process Optimization and Integration","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control reconfiguration; Sequence (biology); Graph; Computer science; Space (punctuation); Theoretical computer science; Topology (electrical circuits); Mathematics; Combinatorics","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002958068,0.0002704191,0.0002568974,0.0001967895,0.0001178155,0.0001010657,0.0004529596,0.0003132029,0.001743508],"category_scores_gemma":[0.0004236295,0.0003066303,0.00008332774,0.00007057296,0.00002151886,0.0002805219,0.0002354532,0.0005617097,0.003794378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002081118,"about_ca_system_score_gemma":0.00005496573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002882603,"about_ca_topic_score_gemma":0.00002491925,"domain_scores_codex":[0.9986467,0.00002834009,0.0003727975,0.0005648991,0.0001876841,0.0001995862],"domain_scores_gemma":[0.99835,0.000008221671,0.0001312285,0.001167229,0.000229078,0.0001142264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004309756,0.00005902862,0.007206609,0.0004583912,0.0001576623,0.000002257729,0.001581589,0.91538,0.03470726,0.001086983,0.02456483,0.0147523],"study_design_scores_gemma":[0.0003925189,0.00003017274,0.05261655,0.0003527032,0.00009054149,0.00001089169,0.00008938534,0.1331313,0.4629186,0.003171084,0.3456973,0.001498981],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5359479,0.0002875169,0.1616221,0.01144688,0.01680391,0.002506123,0.00007109252,0.003731214,0.2675833],"genre_scores_gemma":[0.9913515,0.0003117663,0.001021455,0.00009019027,0.001936407,0.0002656631,0.0002701718,0.00006180034,0.004691044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7822487,"threshold_uncertainty_score":0.9999386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07780052751492263,"score_gpt":0.3194496127273931,"score_spread":0.2416490852124705,"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."}}