{"id":"W7011329170","doi":"","title":"Meta Platforms, Inc. (META) Partners with VSParticle and University of Toronto to Advance Clean Energy Solutions Using AI and Nanotech","year":2024,"lang":"en","type":"other","venue":"","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Clean energy; Energy (signal processing); Clean technology; Efficient energy use","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001530627,0.001547877,0.0006389027,0.001512943,0.0024062,0.003402619,0.001514559,0.00179753,0.2278647],"category_scores_gemma":[0.00130865,0.0006314869,0.0006452983,0.001530424,0.001098772,0.002950754,0.00273949,0.002366905,0.08087168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004487869,"about_ca_system_score_gemma":0.005805264,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05267147,"about_ca_topic_score_gemma":0.1259347,"domain_scores_codex":[0.9991943,0.00004124696,0.00001184328,0.0001099345,0.0004925894,0.000150234],"domain_scores_gemma":[0.9985129,0.0001482705,0.00005229196,0.0002172197,0.0006532934,0.0004161097],"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":[0.0003352338,0.000116816,0.001101023,0.0003798707,0.00002794389,0.0001948448,0.0002137894,0.001197907,0.01785024,0.05783503,0.8124095,0.1083378],"study_design_scores_gemma":[0.00006693531,0.00007457615,0.0006260218,0.00005458617,0.00001498338,0.00008622248,0.0001485835,0.004236462,0.009092503,0.005852821,0.9797236,0.00002278511],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00736304,0.002800706,0.03620756,0.008609712,0.001959468,0.0002978666,0.01556891,0.02265649,0.9045363],"genre_scores_gemma":[0.05513309,0.002410752,0.04679696,0.001330474,0.0002581553,0.00027574,0.01803382,0.006970462,0.8687904],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9473285,"threshold_uncertainty_score":0.7622834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03120438608696606,"score_gpt":0.2520819691013456,"score_spread":0.2208775830143795,"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."}}