{"id":"W4399145144","doi":"10.2139/ssrn.4846835","title":"A Novel Joint-Teaching Sparse Learning by Fractional Function and Generalized Fused Lasso to Identify Dynamical Systems","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Lasso (programming language); Joint (building); Applied mathematics; Function (biology); Mathematics; Artificial intelligence; Computer science; Machine learning; 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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001306279,0.0003956357,0.0004504004,0.0002207842,0.0004293491,0.0006801738,0.0001657663,0.0002149917,0.00008321552],"category_scores_gemma":[0.00001362401,0.0003745925,0.000276823,0.00009900674,0.00002598427,0.000126728,0.0003114434,0.01090294,0.00004551161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006763326,"about_ca_system_score_gemma":0.0007408682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005394319,"about_ca_topic_score_gemma":0.00002641081,"domain_scores_codex":[0.9968089,0.0002316343,0.0005540209,0.0006070143,0.0004176146,0.001380812],"domain_scores_gemma":[0.9991364,0.00003947612,0.0003387889,0.0001661531,0.00008263091,0.0002365035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005182337,0.0005464094,0.001620014,0.0001851627,0.004008152,0.000005964697,0.0003824354,0.2986674,0.06836875,0.5704698,0.01304866,0.04217905],"study_design_scores_gemma":[0.003439991,0.0006206197,0.0006049498,0.001043086,0.001086046,0.0008217922,0.002986317,0.5874769,0.0000874242,0.3726726,0.02704535,0.002114863],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4945266,0.002021212,0.4986065,0.0009654912,0.003030227,0.0002971357,0.00002949628,0.00008315805,0.0004401557],"genre_scores_gemma":[0.9897125,0.0002547783,0.0001228705,0.00004660976,0.00306792,0.0000471364,0.0001516358,0.00007642276,0.006520158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4984837,"threshold_uncertainty_score":0.9998706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01737027029458459,"score_gpt":0.2789933283340848,"score_spread":0.2616230580395002,"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."}}