{"id":"W4368755068","doi":"10.4230/lipics.approx/random.2023.4","title":"Experimental Design for Any $p$-Norm","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fuzhou University; Natural Science Foundation of Fujian Province","keywords":"Norm (philosophy); Mathematical optimization; Mathematics; Interpolation (computer graphics); Computer science; Algorithm; Applied mathematics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01687233,0.001849647,0.001590539,0.0009263227,0.0005638583,0.001858114,0.002146011,0.002347766,0.005409485],"category_scores_gemma":[0.04209809,0.0007593141,0.001329249,0.0008931133,0.003207294,0.004109531,0.002589794,0.004025696,0.0009302456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00150336,"about_ca_system_score_gemma":0.002101261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000455802,"about_ca_topic_score_gemma":0.0004327767,"domain_scores_codex":[0.9883663,0.007128606,0.0004883923,0.00227602,0.001416059,0.0003246175],"domain_scores_gemma":[0.9673258,0.02428538,0.002731446,0.003416845,0.001517787,0.0007227171],"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":[0.0009218627,0.0004182613,0.001493448,0.001031957,0.0002435621,0.0001599745,0.0001236395,0.3721553,0.01508917,0.4719746,0.003123993,0.1332642],"study_design_scores_gemma":[0.0001384003,0.001007843,0.00037386,0.00009090234,0.00006046704,0.0001102711,0.00004232252,0.620774,0.007914388,0.3628725,0.006575574,0.00003950246],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003266327,0.0001690716,0.994007,0.0002866916,0.00003905665,0.00007309669,0.00005363533,0.000103607,0.00200142],"genre_scores_gemma":[0.1560919,0.0005364057,0.8376375,0.0006887927,0.0001292928,0.001238266,0.0002553233,0.0001576437,0.003264893],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01687233,"threshold_uncertainty_score":0.08923048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1123993981993143,"score_gpt":0.1900509867269578,"score_spread":0.07765158852764358,"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."}}