{"id":"W2056770340","doi":"10.1142/s0219477503001543","title":"A TIME-DOMAIN APPROACH TO EXTRACTING POLARIZATION RESISTANCE FROM ELECTROCHEMICAL NOISE DATA","year":2003,"lang":"en","type":"article","venue":"Fluctuation and Noise Letters","topic":"Corrosion Behavior and Inhibition","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Electrochemical noise; Polarization (electrochemistry); Corrosion; Time domain; Materials science; Electrode; Electrochemistry; Computer science; Noise (video); Electronic engineering; Metallurgy; Physics; Engineering; Artificial intelligence; Chemistry","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":[0.0003615438,0.0001269047,0.0001265284,0.0000656819,0.0001680189,0.0001193219,0.0001552936,0.00005989244,0.0002672306],"category_scores_gemma":[0.0001984293,0.0001281982,0.00001808448,0.0001735694,0.00003937346,0.0004300131,0.0000506536,0.00009403325,0.0001337246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004767763,"about_ca_system_score_gemma":0.00002066594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000125754,"about_ca_topic_score_gemma":0.000004176556,"domain_scores_codex":[0.9986975,0.0001178007,0.0002285538,0.00049544,0.0002580936,0.000202681],"domain_scores_gemma":[0.9993396,0.00005950652,0.00008103779,0.0003834685,0.00003518076,0.0001011412],"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":[0.00004082088,0.00003663257,0.00008056305,0.000004637066,5.5115e-7,6.480643e-7,0.0003305004,0.000006872431,0.9952158,0.00009563403,0.004085072,0.0001022548],"study_design_scores_gemma":[0.0006435908,0.00001894774,0.001819833,0.00004268724,0.00003490758,0.000007269826,0.0001430001,0.001213763,0.9896045,0.0002055568,0.005897911,0.0003680146],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8798004,0.0000315319,0.1183568,0.0009669308,0.000092146,0.0002113816,0.00004583911,0.0000632955,0.0004317128],"genre_scores_gemma":[0.9680241,0.000002557195,0.02836891,0.002573806,0.0001064793,0.00002128199,0.0006821872,0.00001910603,0.0002015658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08998787,"threshold_uncertainty_score":0.5227769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01962743625295437,"score_gpt":0.2434122852874693,"score_spread":0.223784849034515,"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."}}