{"id":"W4410290368","doi":"10.1021/acsami.5c02198","title":"Chronopotentiometric Approach in Scanning Electrochemical Cell Microscopy: Minimizing Surface Change Upon Landing","year":2025,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; McGill University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Centre québécois de recherche et de développement de l’aluminium; Nurse Practitioners of Oregon","keywords":"Materials science; Scanning electrochemical microscopy; Electrochemistry; Scanning electron microscope; Scanning probe microscopy; Microscopy; Scanning ion-conductance microscopy; Nanotechnology; Chemical engineering; Scanning confocal electron microscopy; Electrode; Optics; Composite material; Physical chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009739599,0.000709497,0.0004298997,0.0006184502,0.0003359258,0.0008931737,0.001726487,0.001138249,0.001618742],"category_scores_gemma":[0.001743739,0.0005178144,0.0002182747,0.000598438,0.0007492065,0.001354039,0.0006564407,0.001613061,0.0007528124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005996219,"about_ca_system_score_gemma":0.0004960286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005207135,"about_ca_topic_score_gemma":0.001644914,"domain_scores_codex":[0.9989975,0.0001262933,0.0000465526,0.000264591,0.0004949927,0.00007005843],"domain_scores_gemma":[0.9991063,0.0003719502,0.0001576563,0.0001185692,0.0002102261,0.00003523751],"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":[0.00002446072,0.00002569355,0.00009870908,0.0001458922,0.00000353168,0.0000505176,0.00005691727,0.00009742994,0.9889227,0.0007411662,0.0002601297,0.009572843],"study_design_scores_gemma":[0.000009003887,0.0001443002,0.0007134236,0.00001227921,0.000006680664,0.0003182758,0.0000437083,0.00434194,0.9892824,0.000284065,0.004821483,0.00002244968],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2607407,0.009127856,0.7156736,0.0009742692,0.0009601163,0.0006304324,0.0006127759,0.002543431,0.008736721],"genre_scores_gemma":[0.4790182,0.006831508,0.5059919,0.0005815105,0.0001476169,0.0007014553,0.0003205346,0.0002349602,0.006172363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001726487,"threshold_uncertainty_score":0.005415261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01382198429884669,"score_gpt":0.2598741071442027,"score_spread":0.246052122845356,"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."}}