{"id":"W4403498726","doi":"10.22541/au.172914739.97186665/v1","title":"on “AutoRepar: A method to obtain identifiable and observable reparameterizations of dynamic models with mechanistic insights”: Existence of an identifiable reparameterization","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Observable; Statistical physics; Econometrics; Mathematical economics; Computer science; Applied mathematics; Theoretical physics; Mathematics; Physics; Quantum mechanics","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":[0.005708418,0.001589839,0.001566842,0.001843756,0.001251689,0.001626033,0.002309694,0.002199278,0.007820024],"category_scores_gemma":[0.01578694,0.001128682,0.002800183,0.0008620795,0.004509225,0.005328517,0.006410251,0.004695276,0.00179527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008873204,"about_ca_system_score_gemma":0.001087065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005644915,"about_ca_topic_score_gemma":0.001021766,"domain_scores_codex":[0.9981751,0.000809556,0.0001024155,0.0004168501,0.0003900127,0.0001059596],"domain_scores_gemma":[0.9932426,0.003812341,0.0006354657,0.001721527,0.0003951891,0.000192897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001615214,0.00009283661,0.0006950386,0.0003012172,0.0001393696,0.0003489302,0.0005702669,0.101305,0.008541103,0.7984006,0.001931048,0.08751323],"study_design_scores_gemma":[0.00002951115,0.0001263294,0.0001808893,0.00004782856,0.00003121621,0.0001481604,0.0000785579,0.509083,0.004499559,0.4808251,0.004879321,0.00007048677],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002729532,0.00005011815,0.9960744,0.00007864191,0.00001294786,0.00002726675,0.00002890636,0.0001729315,0.0008252868],"genre_scores_gemma":[0.1633525,0.0004267671,0.8281272,0.000344749,0.0001532762,0.0005528647,0.0003684271,0.0007555205,0.005918713],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007820024,"threshold_uncertainty_score":0.03018934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02272030645448421,"score_gpt":0.3013411536496978,"score_spread":0.2786208471952136,"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."}}