{"id":"W4388112906","doi":"10.3390/f14112175","title":"Impregnation of Medium-Density Fiberboard Residues with Phase Change Materials for Efficient Thermal Energy Storage","year":2023,"lang":"en","type":"article","venue":"Forests","topic":"Phase Change Materials Research","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Thermogravimetric analysis; Materials science; Fiberboard; Fourier transform infrared spectroscopy; Differential scanning calorimetry; Thermal stability; Scanning electron microscope; Composite material; Porosity; Chemical 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":[],"consensus_categories":[],"category_scores_codex":[0.0003593898,0.0001402223,0.0002279211,0.0002047715,0.00004358868,0.00002795071,0.0001453866,0.00007431058,0.00007191432],"category_scores_gemma":[0.00004362173,0.0001176419,0.00003079069,0.0002161958,0.00004307159,0.00008064784,0.00005437736,0.00003100116,0.00001519393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006793447,"about_ca_system_score_gemma":0.00002011955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001021965,"about_ca_topic_score_gemma":0.0005788772,"domain_scores_codex":[0.9989343,0.00003641703,0.0001852263,0.0001611463,0.0003487727,0.0003341096],"domain_scores_gemma":[0.9994649,0.00006991141,0.00004569949,0.0002256587,0.00012511,0.00006866403],"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":[0.0003305541,0.00005021014,0.00003061477,0.0004449053,0.0000455881,0.0000256816,0.0008263665,0.002732239,0.9924406,0.0001476888,0.001448444,0.001477108],"study_design_scores_gemma":[0.001245935,0.0002330991,0.006824172,0.0001005039,0.00001240282,0.000001994898,0.0000212308,0.01020651,0.980781,0.00006483209,0.0003674051,0.0001409404],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997537,0.00007205083,0.0008283664,0.00004869661,0.0003816619,0.0004375368,0.0003545397,0.0002846339,0.00005558105],"genre_scores_gemma":[0.9988713,0.00002566185,0.0000736441,0.000006808817,0.0003280285,0.000352503,0.0002347068,0.00005643952,0.00005087769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01165963,"threshold_uncertainty_score":0.4797298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04343160282446404,"score_gpt":0.2979125042115175,"score_spread":0.2544809013870535,"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."}}