{"id":"W2084662594","doi":"10.1080/10407790903508129","title":"Inverse Identification of Thermal Properties of Charring Ablators","year":2010,"lang":"en","type":"article","venue":"Numerical Heat Transfer Part B Fundamentals","topic":"Gas Dynamics and Kinetic Theory","field":"Mathematics","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Charring; Heat flux; Materials science; Mechanics; Thermal conductivity; Mass flux; Flux (metallurgy); Mass flow rate; Combustion; Pyrolysis; Thermodynamics; Inverse; Heat transfer; Chemistry; Composite material; Mathematics; Physics; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006633021,0.0005355275,0.0006881679,0.0006847588,0.0002805973,0.0008382685,0.0006629574,0.0006344845,0.001342706],"category_scores_gemma":[0.002173093,0.000402152,0.0005070993,0.0004946657,0.0005559145,0.001014023,0.0006347119,0.0009339525,0.0006972197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003556869,"about_ca_system_score_gemma":0.0007697271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004689783,"about_ca_topic_score_gemma":0.0004935354,"domain_scores_codex":[0.9994997,0.0000826801,0.00001780702,0.0001225581,0.0002451871,0.00003205934],"domain_scores_gemma":[0.9994903,0.0001940511,0.00006642906,0.00007444827,0.0001588161,0.00001596726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001982142,0.00008568283,0.001783875,0.0003454309,0.00003507508,0.0002395066,0.0003345733,0.4577533,0.3635506,0.0232837,0.0008750641,0.1515148],"study_design_scores_gemma":[0.000005103225,0.00002832713,0.0005867372,0.000006843683,0.000005651267,0.00007620535,0.00001754723,0.9545114,0.03914505,0.004470523,0.001129286,0.00001741186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0496431,0.0001263964,0.947567,0.00004104407,0.00001730859,0.00002459017,0.00005835563,0.0003658246,0.002156295],"genre_scores_gemma":[0.6710878,0.0003628152,0.3228201,0.00003122336,0.00001998242,0.0001322863,0.0002480396,0.0002408452,0.005056984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001342706,"threshold_uncertainty_score":0.004491806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03382433824767903,"score_gpt":0.2666696882878071,"score_spread":0.2328453500401281,"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."}}