{"id":"W4409187835","doi":"10.1002/9781394294404.ch7","title":"Quantile Regression Using Log‐Cosh","year":2025,"lang":"en","type":"other","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of British Columbia","funders":"","keywords":"Quantile regression; Statistics; Quantile; Regression; Computer science; Regression analysis; Econometrics; Mathematics","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":[0.004154556,0.000888543,0.0008603049,0.001205172,0.0004072352,0.002035906,0.001502982,0.001033347,0.008808844],"category_scores_gemma":[0.01759916,0.0003481753,0.0007789603,0.002175499,0.001174573,0.002105285,0.001880252,0.00251622,0.003545163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009414128,"about_ca_system_score_gemma":0.001089721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004120482,"about_ca_topic_score_gemma":0.002486274,"domain_scores_codex":[0.9980895,0.000872174,0.00007720525,0.0003052659,0.0005193343,0.000136426],"domain_scores_gemma":[0.9958214,0.002658195,0.0003792318,0.0005767552,0.0004644406,0.00009996729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002309262,0.00009922071,0.01001691,0.0003141917,0.000169591,0.0002329061,0.0001956954,0.3403081,0.002443861,0.2272578,0.02560647,0.3931244],"study_design_scores_gemma":[0.00002105037,0.00007024282,0.003143009,0.00007669908,0.00003116067,0.000150571,0.00006736774,0.8828053,0.001816789,0.09031487,0.02146224,0.00004068189],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006563095,0.001110707,0.9856269,0.0006107101,0.0001214232,0.00003761907,0.0003922226,0.001350166,0.00418724],"genre_scores_gemma":[0.5700515,0.006171345,0.3878168,0.001109659,0.0006584397,0.0003943887,0.002922024,0.001854041,0.02902178],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008808844,"threshold_uncertainty_score":0.02946854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03042386681035611,"score_gpt":0.2989804021778419,"score_spread":0.2685565353674859,"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."}}