{"id":"W4409749052","doi":"10.1002/ese3.70110","title":"End‐To‐End Deep Learning Temperature Prediction Algorithms of a Phase Change Materials From Experimental Photos","year":2025,"lang":"en","type":"article","venue":"Energy Science & Engineering","topic":"Phase Change Materials Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Balsillie School of International Affairs; University of Waterloo","funders":"","keywords":"Algorithm; Phase change; Artificial intelligence; Deep learning; Computer science; Engineering physics; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000341597,0.0002482338,0.0002972455,0.0006541578,0.0001164255,0.0001501106,0.0004384317,0.0001006466,0.0002911873],"category_scores_gemma":[0.00007772588,0.0002639659,0.00003926034,0.00100231,0.0000840873,0.0004858723,0.0001749651,0.0001445433,0.000006859065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002536534,"about_ca_system_score_gemma":0.00003215953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002899673,"about_ca_topic_score_gemma":0.000007045044,"domain_scores_codex":[0.9982679,0.00002365033,0.0003107977,0.000386743,0.0004643485,0.0005465012],"domain_scores_gemma":[0.9994063,0.00004003912,0.00002875253,0.0002841708,0.00006354734,0.0001771989],"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":[0.00001435555,0.00003622462,0.000005590625,0.00001298129,0.00002009898,0.000008162488,0.0008227959,0.0243908,0.9722217,0.0009224244,0.00001541176,0.001529468],"study_design_scores_gemma":[0.0004751692,0.00007599826,0.0002181923,0.0001248984,0.000006273218,0.000002575852,0.000139661,0.05004217,0.9443184,0.000004511623,0.00440595,0.0001862552],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900736,0.0009325515,0.00621426,0.00001379298,0.001844522,0.0001964004,0.0001259258,0.0003833817,0.0002155963],"genre_scores_gemma":[0.9978789,0.00005504108,0.001303726,0.00002154702,0.0003476899,0.0002561538,0.00005424198,0.00003984675,0.00004282051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02790334,"threshold_uncertainty_score":0.9999813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01634901937126462,"score_gpt":0.2779070289561909,"score_spread":0.2615580095849263,"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."}}