{"id":"W4287444239","doi":"","title":"Plasma Etching: an Enabler to Better Concentrated Photovoltaics Systems","year":2021,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"solar cell performance optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Photovoltaics; Etching (microfabrication); Enabling; Plasma; Optoelectronics; Materials science; Plasma etching; Engineering physics; Environmental science; Computer science; Nanotechnology; Electrical engineering; Photovoltaic system; Engineering; Physics","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":[0.0002894074,0.0003346239,0.0005229167,0.0001506679,0.0002491596,0.0009813687,0.0005923674,0.001087737,0.008495688],"category_scores_gemma":[0.0002945645,0.0002286318,0.0002564491,0.0003390984,0.0003237765,0.0009444589,0.0007256147,0.0007396336,0.001456298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004648341,"about_ca_system_score_gemma":0.0002200188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003084754,"about_ca_topic_score_gemma":0.000396512,"domain_scores_codex":[0.9998382,0.00001317552,0.000003914281,0.00004139226,0.00008417312,0.00001914885],"domain_scores_gemma":[0.9999043,0.00003152901,0.000009794291,0.00001608547,0.00003064982,0.000007750863],"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":[0.0002863708,0.0001529624,0.0005489127,0.000626551,0.0001003524,0.0001755449,0.0001520837,0.018407,0.8231215,0.03465861,0.0103571,0.1114131],"study_design_scores_gemma":[0.0001538006,0.0006790253,0.002720467,0.00007366747,0.00009868803,0.0005897558,0.0001473543,0.1015871,0.7119617,0.04106543,0.1408611,0.00006182398],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.48661,0.03278023,0.3302229,0.008767829,0.00162721,0.0001682433,0.001054581,0.002094173,0.1366749],"genre_scores_gemma":[0.8594574,0.009814753,0.07021631,0.0006808028,0.0006111529,0.00007146219,0.0005618284,0.0004407466,0.05814558],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.008495688,"threshold_uncertainty_score":0.02842093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01190975199896274,"score_gpt":0.202837788671006,"score_spread":0.1909280366720432,"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."}}