{"id":"W2602729393","doi":"10.1149/ma2006-02/39/1786","title":"Intelligent Electrodes to Distinguish between Wanted and Unwanted Reactions","year":2006,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Electrode; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006552056,0.0007427222,0.0006927375,0.0004782763,0.0003507503,0.001329005,0.001608472,0.001879458,0.009645078],"category_scores_gemma":[0.001333498,0.0004376374,0.0005557876,0.0003217717,0.0003304144,0.001265353,0.0004850423,0.001524159,0.004440419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002199764,"about_ca_system_score_gemma":0.000133258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001398926,"about_ca_topic_score_gemma":0.0003879775,"domain_scores_codex":[0.9995207,0.0000644519,0.00003240323,0.0001190372,0.0002130123,0.00005043199],"domain_scores_gemma":[0.999368,0.0002092937,0.00006112207,0.0001229555,0.0001845005,0.00005404322],"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":[0.0003824791,0.0001102369,0.0004131952,0.0004423393,0.00005023921,0.0002119319,0.0000389625,0.0002309305,0.9478483,0.001645546,0.004536448,0.04408937],"study_design_scores_gemma":[0.00004366475,0.000255158,0.001031864,0.00004354067,0.00009119194,0.0008192675,0.00002392375,0.005868108,0.9722176,0.0007461935,0.01883469,0.00002486951],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4374749,0.04390457,0.426375,0.006183474,0.005335192,0.0009281617,0.002946405,0.007938488,0.06891371],"genre_scores_gemma":[0.7775655,0.006902499,0.1549704,0.002081148,0.0004156044,0.0003480166,0.002327474,0.0004566738,0.05493266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009645078,"threshold_uncertainty_score":0.03226596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0114884937477285,"score_gpt":0.2512090769113246,"score_spread":0.2397205831635961,"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."}}