{"id":"W4389298617","doi":"10.1016/j.joule.2023.11.006","title":"Historical market projections and the future of silicon solar cells","year":2023,"lang":"en","type":"article","venue":"Joule","topic":"Silicon and Solar Cell Technologies","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Royal Academy of Engineering; Australian Renewable Energy Agency; Canada Excellence Research Chairs, Government of Canada; Commonwealth Scientific and Industrial Research Organisation; Australian Government","keywords":"Silicon solar cell; Silicon valley; Engineering physics; Silicon; Materials science; Engineering; Forensic engineering; Nanotechnology; Business; Optoelectronics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001269273,0.00005135083,0.00009980927,0.00006991808,0.00004076656,0.000008210828,0.00007137478,0.00007471578,0.00002669814],"category_scores_gemma":[0.00001668049,0.00003477427,0.00004717712,0.0002239202,0.00003870284,0.00002582705,0.00002794837,0.0001321817,0.00001099291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003011098,"about_ca_system_score_gemma":0.000004274026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001399114,"about_ca_topic_score_gemma":0.00001140849,"domain_scores_codex":[0.9996981,0.00001325048,0.00008780285,0.00005785673,0.00005366837,0.00008929815],"domain_scores_gemma":[0.9997783,0.0000507357,0.00001183657,0.0001387386,0.000007301225,0.00001304096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004512384,0.00004354199,0.005560709,0.0003010627,0.00014953,0.00001245799,0.002310583,0.0005001948,0.05078071,0.003157852,0.8780367,0.0591015],"study_design_scores_gemma":[0.0008190426,0.00003837447,0.01081671,0.00001186145,0.000031282,0.000007751342,0.001958166,0.02705013,0.02545487,0.0009593057,0.9326748,0.0001777584],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712752,0.003908744,0.00008897522,0.001611064,0.001457565,0.0002768298,0.000005198281,0.001379938,0.01999656],"genre_scores_gemma":[0.9942611,0.002476692,0.00009029358,0.00001772098,0.0001074287,0.00002371666,6.159834e-7,0.00001571443,0.003006711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05892374,"threshold_uncertainty_score":0.1418054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008039878459331708,"score_gpt":0.1959274921919214,"score_spread":0.1878876137325897,"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."}}