{"id":"W4390786546","doi":"","title":"TRIGONOMETRIC MELNIKOV PRODUCTS: EXTENSION, DERIVATION AND EVALUATION","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Material Properties and Applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Extension (predicate logic); Trigonometry; Mathematics; Computer science; Mathematical analysis; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.001410447,0.0001788984,0.0002290175,0.0002045894,0.0001541098,0.0002899318,0.0001999427,0.0001404805,0.0008979769],"category_scores_gemma":[0.0005255117,0.0001409314,0.00002506087,0.0003317005,0.00005689547,0.0001091197,0.0006051083,0.00009893849,0.0004519937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006974411,"about_ca_system_score_gemma":0.0001283177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004027472,"about_ca_topic_score_gemma":0.00001121517,"domain_scores_codex":[0.9982528,0.00009576209,0.0003935823,0.0007255255,0.0003512712,0.0001810732],"domain_scores_gemma":[0.998637,0.00004009461,0.0001975237,0.000595872,0.0004760563,0.00005341599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003700672,0.00007446938,0.00005694012,0.0005179909,0.00001497603,5.667555e-7,0.0002209654,0.00128292,0.9630511,0.002559787,0.01426444,0.01791886],"study_design_scores_gemma":[0.001423715,0.0001668683,0.05045961,0.0003851549,0.0003724876,0.00001346893,0.0004846528,0.05425197,0.7914937,0.07584099,0.02323181,0.001875527],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904136,0.0004033289,0.001748874,0.003409804,0.001262482,0.001609971,0.00003842854,0.0003489028,0.0007645751],"genre_scores_gemma":[0.9924483,0.0002237575,0.004178888,0.00009738537,0.0003558314,0.0006447554,0.0001907962,0.00003287936,0.001827417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1715573,"threshold_uncertainty_score":0.9832217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1243867135659803,"score_gpt":0.3168810212143151,"score_spread":0.1924943076483348,"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."}}