{"id":"W4398781574","doi":"10.3390/en17112538","title":"Multi-Terminal GaInP/GaInAs/Ge Solar Cells for Subcells Characterization","year":2024,"lang":"en","type":"article","venue":"Energies","topic":"solar cell performance optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Centre National de la Recherche Scientifique; Institut National des Sciences Appliquées de Lyon; Université Grenoble Alpes; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Indian National Science Academy","keywords":"Fabrication; Optoelectronics; Materials science; Solar cell; Wafer; Characterization (materials science); Triple junction; Diode; Electroluminescence; Absorption (acoustics); Nanotechnology; Layer (electronics); Composite material","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":[0.0001353928,0.0002269728,0.0002261692,0.0002658341,0.0002366504,0.0003217855,0.0002711443,0.0002524393,0.0009018634],"category_scores_gemma":[0.0001223369,0.000111269,0.0001601233,0.0002739465,0.0001311673,0.0002574768,0.0002022767,0.0002697473,0.0002413879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002251178,"about_ca_system_score_gemma":0.0001198852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008449773,"about_ca_topic_score_gemma":0.002781289,"domain_scores_codex":[0.9998771,0.000008145063,0.000004681743,0.00003500227,0.00006138763,0.00001372983],"domain_scores_gemma":[0.999911,0.00002269371,0.00001178162,0.00001818422,0.00003092809,0.000005547253],"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":[0.00001499911,0.000007664683,0.0006741092,0.00001756268,0.000003355209,0.00003194514,0.00002429915,0.0004918293,0.9969391,0.00012889,0.00003076444,0.001635515],"study_design_scores_gemma":[0.000001309758,0.00004888099,0.005451324,0.00000285964,0.000008381154,0.00007830477,0.00003985587,0.01014416,0.9834199,0.00006947297,0.0007303406,0.000005287642],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799883,0.0004112869,0.0170391,0.00003052048,0.00001118676,0.00002637547,0.0004016587,0.0001085566,0.001983003],"genre_scores_gemma":[0.987469,0.0001423625,0.01151521,0.00001371089,0.000002872378,0.00002993963,0.0001442295,0.00001628647,0.0006663642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009018634,"threshold_uncertainty_score":0.003017068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01041058343885555,"score_gpt":0.2167868583605436,"score_spread":0.2063762749216881,"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."}}