{"id":"W2963713621","doi":"10.1007/s10473-019-0304-5","title":"On the Necessary and Sufficient Conditions to Solve A Heat Equation with General Additive Gaussian Noise","year":2019,"lang":"en","type":"article","venue":"Acta Mathematica Scientia","topic":"Numerical methods in inverse problems","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Heat equation; Gaussian noise; Gaussian; Mathematics; Applied mathematics; Noise (video); Mathematical analysis; Computer science; Physics; Algorithm; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001043364,0.0002399648,0.000309117,0.0001556928,0.0002892729,0.0001930461,0.0003439701,0.00006059736,0.001497837],"category_scores_gemma":[0.0009543692,0.0001410577,0.00006396502,0.0005695865,0.0002399361,0.0001940272,0.0001719453,0.0002052813,0.0004228938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006621728,"about_ca_system_score_gemma":0.00005290181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009089011,"about_ca_topic_score_gemma":0.000004351731,"domain_scores_codex":[0.9980277,0.0001306031,0.0003304338,0.0004784196,0.0006276773,0.000405167],"domain_scores_gemma":[0.9965003,0.002334453,0.00013592,0.0007284667,0.0001124907,0.0001884369],"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":[0.0000359721,0.0003566954,0.0000314165,0.0001166233,0.00007226765,0.000003460044,0.00371585,0.00007994247,0.01034471,0.9701403,0.01498579,0.0001169765],"study_design_scores_gemma":[0.0009215094,0.0008081985,0.0003813873,0.0008201114,0.0002076753,0.00005276095,0.002242976,0.03983114,0.01069783,0.9420409,0.001298725,0.0006967647],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8968937,0.000006011658,0.0702462,0.004527018,0.0002663012,0.001968028,0.00007576984,0.0001150426,0.02590192],"genre_scores_gemma":[0.7717183,0.000001727983,0.225781,0.001024735,0.00003755952,0.0002072916,0.0000103993,0.00004484868,0.001174201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1555348,"threshold_uncertainty_score":0.9994149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04716439499205029,"score_gpt":0.3188236996798905,"score_spread":0.2716593046878403,"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."}}