{"id":"W4320185827","doi":"10.2139/ssrn.4355729","title":"Partial Envelope Tensor Response Regression","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Envelope (radar); Regression; Mathematics; Tensor (intrinsic definition); Statistics; Computer science; Pure mathematics; Telecommunications","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":[0.002715139,0.001595131,0.001301463,0.001095076,0.0006677853,0.001992756,0.001395919,0.00201843,0.01911993],"category_scores_gemma":[0.009826807,0.000609462,0.00165869,0.001595545,0.0008986489,0.001911664,0.002012612,0.003119755,0.01750728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004459175,"about_ca_system_score_gemma":0.00156684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002394206,"about_ca_topic_score_gemma":0.002765312,"domain_scores_codex":[0.9984778,0.0006274398,0.00005190334,0.0003570104,0.0003374568,0.0001484082],"domain_scores_gemma":[0.9964656,0.0009414468,0.0002057126,0.001433183,0.0007719407,0.0001822153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006932532,0.0003335371,0.002641757,0.0003473904,0.0003855929,0.0002804109,0.0001373308,0.173018,0.0200785,0.09271701,0.07916225,0.630205],"study_design_scores_gemma":[0.00002658941,0.00009289692,0.0009462779,0.00004838176,0.00006187873,0.0001543586,0.00004529628,0.9417169,0.007294884,0.02968134,0.01988239,0.00004878104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01229103,0.0004909349,0.974478,0.0007733451,0.0003983067,0.00009570159,0.001216313,0.003960799,0.006295561],"genre_scores_gemma":[0.3372808,0.001277498,0.5560744,0.001186455,0.0008153136,0.0003469801,0.007889253,0.003832636,0.09129661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01911993,"threshold_uncertainty_score":0.06396252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01532969834488109,"score_gpt":0.281826903833466,"score_spread":0.2664972054885849,"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."}}