{"id":"W4220771592","doi":"10.1002/wics.1580","title":"Function minimization and nonlinear least squares in R","year":2022,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Computational Statistics","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Minification; Non-linear least squares; Nonlinear programming; Mathematical optimization; Context (archaeology); Computer science; Nonlinear system; Perspective (graphical); Least-squares function approximation; Function (biology); Implementation; Algorithm; Mathematics; Estimation theory; Artificial intelligence; Statistics","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008075165,0.000632713,0.002040896,0.0006712206,0.000358561,0.0001025845,0.0003720786,0.0001879026,0.001166903],"category_scores_gemma":[0.0008981244,0.0005876693,0.0002303564,0.0009684564,0.0001569861,0.0002178663,0.001108955,0.0008952989,0.00008400596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005141045,"about_ca_system_score_gemma":0.0002785016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001426163,"about_ca_topic_score_gemma":0.00002102422,"domain_scores_codex":[0.9953165,0.0009988963,0.001821747,0.0007988027,0.0006752583,0.0003888202],"domain_scores_gemma":[0.9955247,0.002779695,0.001013949,0.0003755732,0.0001524656,0.000153587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002109543,0.000193597,0.0000026744,0.01409311,0.00006190009,0.0000371685,0.0001811164,0.0030901,3.26298e-9,0.006622327,0.01173647,0.9639604],"study_design_scores_gemma":[0.0003018583,0.0001549461,0.000002594091,0.006239644,0.0002516398,0.00009720548,0.00009157307,0.06310919,2.615055e-9,0.04535395,0.8838857,0.0005117281],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[1.669406e-7,0.6339368,0.363268,0.0000353839,0.000219234,0.001514984,0.0008470656,0.00004430816,0.0001340108],"genre_scores_gemma":[9.011475e-8,0.7188862,0.2760495,0.00002214716,0.0001198611,0.0005009029,0.003904589,0.0001009125,0.0004158512],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9634487,"threshold_uncertainty_score":0.9997461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1448641518111891,"score_gpt":0.4485202495835514,"score_spread":0.3036560977723624,"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."}}