{"id":"W2966106702","doi":"10.1007/978-3-030-17519-1_10","title":"Penalized Relative Error Estimation of a Partially Functional Linear Multiplicative Model","year":2019,"lang":"en","type":"book-chapter","venue":"Contributions to statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University","funders":"","keywords":"Multiplicative function; Estimation; Mathematics; Applied mathematics; Approximation error; Statistics; Econometrics; Algorithm; Computer science; Economics; Mathematical analysis","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004835933,0.0004233535,0.0009411526,0.0001738078,0.0001367984,0.00002116565,0.0002042121,0.0003712373,0.0008885964],"category_scores_gemma":[0.0162705,0.0004085369,0.0001365518,0.0000967609,0.00023388,0.00006534049,0.000132235,0.0005050554,0.0003875776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002754883,"about_ca_system_score_gemma":0.0008487775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007754527,"about_ca_topic_score_gemma":0.00001390778,"domain_scores_codex":[0.9974965,0.00009372345,0.001068529,0.0004901597,0.000538912,0.0003121826],"domain_scores_gemma":[0.9904328,0.005197081,0.0007475503,0.0005778773,0.002832007,0.0002126608],"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":[0.0001368002,0.00006717597,0.000001278818,0.0001154469,0.000184042,0.000002913238,0.0001209115,0.006135594,0.00004037644,0.9805406,0.01003156,0.002623338],"study_design_scores_gemma":[0.0005269113,0.0001438601,0.00002080559,0.0002080524,0.0003321115,0.000001951422,0.000004133025,0.3484726,0.00006943413,0.6480855,0.001852943,0.0002817416],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00000438063,0.0000343742,0.9117646,0.0001494048,0.0001587155,0.001177303,0.0491317,0.00005693938,0.03752255],"genre_scores_gemma":[0.002442382,0.00001427427,0.8845342,0.00008175249,0.00007197823,0.00008422085,0.001032769,0.00006791337,0.1116705],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.342337,"threshold_uncertainty_score":0.9998366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1282338785798527,"score_gpt":0.4026128983094234,"score_spread":0.2743790197295707,"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."}}