{"id":"W4387190276","doi":"10.1149/2.f05233if","title":"Tech Highlights - Fall 2023","year":2023,"lang":"en","type":"article","venue":"The Electrochemical Society Interface","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Abbott (Canada)","funders":"","keywords":"Materials 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001079284,0.0001619635,0.0001492824,0.00001069103,0.00009482568,0.00003430625,0.0002902702,0.0001020771,0.00004552036],"category_scores_gemma":[0.00003029898,0.00011698,0.0001065935,0.0003334061,0.00005921313,0.00005295312,0.00006021336,0.0002306702,0.0005365189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000734687,"about_ca_system_score_gemma":0.000003665011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009251046,"about_ca_topic_score_gemma":0.000002197336,"domain_scores_codex":[0.9990932,0.00001284675,0.0001596474,0.0001566299,0.0001285287,0.0004490908],"domain_scores_gemma":[0.9995778,0.0001098386,0.00001743974,0.0002215267,0.00001977401,0.00005357287],"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":[0.000003959149,0.0000034003,0.000001661197,0.00001773221,0.00004054944,5.491109e-7,0.0002043859,0.003628731,0.9713104,0.0001530095,0.02454039,0.00009528313],"study_design_scores_gemma":[0.00009126268,0.00001326427,0.00001646524,0.00001535818,0.000009447621,0.000005554587,0.00006442446,0.007781853,0.961501,0.001314575,0.02902298,0.0001637949],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9430566,0.0004170536,0.04659072,0.001111944,0.0005303221,0.0001495659,0.000007839761,0.003414248,0.004721685],"genre_scores_gemma":[0.9952868,0.0003377711,0.0006733147,0.00009607495,0.0002475422,0.00002665709,0.00001679756,0.00004836384,0.003266718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05223014,"threshold_uncertainty_score":0.6896043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0100863990408522,"score_gpt":0.2321921192245222,"score_spread":0.2221057201836699,"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."}}