{"id":"W4396629696","doi":"10.2139/ssrn.4815518","title":"An Affordable Platform for Automated Synthesis and Electrochemical Characterization","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Characterization (materials science); Electrochemistry; Computer science; Business; Nanotechnology; Chemistry; Materials science; Electrode","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":[0.0008473445,0.001134814,0.001483981,0.001452447,0.0005319435,0.001328617,0.002954616,0.001449711,0.03699903],"category_scores_gemma":[0.002365205,0.0009528401,0.000612914,0.001061781,0.000340276,0.00177388,0.00206478,0.001563623,0.02360566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004393271,"about_ca_system_score_gemma":0.0007300778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006322882,"about_ca_topic_score_gemma":0.001641894,"domain_scores_codex":[0.9985778,0.00008161291,0.00006015177,0.0002676878,0.0009257542,0.00008703496],"domain_scores_gemma":[0.9984062,0.0003257049,0.0001138874,0.0006433006,0.0004089402,0.0001018927],"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":[0.0005129207,0.0003083173,0.0009839599,0.0006696656,0.0001420274,0.0003878511,0.00007482093,0.003631222,0.683478,0.007944157,0.07382031,0.2280468],"study_design_scores_gemma":[0.0002101219,0.0004389898,0.002266712,0.00006734634,0.0001152575,0.001043129,0.00006040838,0.1070345,0.655892,0.01356188,0.2191875,0.0001222426],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02205215,0.0008943006,0.8722403,0.0007066031,0.0006768217,0.0005351898,0.00837535,0.07471751,0.01980183],"genre_scores_gemma":[0.1814497,0.0008422935,0.7576851,0.0007330968,0.0003284879,0.001733394,0.01839333,0.00561998,0.03321454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03699903,"threshold_uncertainty_score":0.1237741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008242495415280032,"score_gpt":0.270306491902627,"score_spread":0.262063996487347,"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."}}