{"id":"W4387142957","doi":"10.1016/j.powtec.2023.119021","title":"Rapid characterization of combustible particle breakage via dry dispersion laser diffraction","year":2023,"lang":"en","type":"article","venue":"Powder Technology","topic":"Combustion and Detonation Processes","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Beijing Institute of Technology; State Key Laboratory of Explosion Science and Technology; National Natural Science Foundation of China","keywords":"Breakage; Dispersion (optics); Particle-size distribution; Particle (ecology); Particle size; Dust explosion; Materials science; Diffraction; Comminution; Mineralogy; Optics; Composite material; Chemistry; Thermodynamics; Physics; Metallurgy; Geology","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":[0.0004944783,0.000339344,0.0005500828,0.001127893,0.0005036727,0.0005912362,0.0006593742,0.0006718885,0.002105817],"category_scores_gemma":[0.0008181285,0.0003487224,0.0002299979,0.000776969,0.0006624868,0.0006320577,0.0004153403,0.0009940701,0.000454624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006699973,"about_ca_system_score_gemma":0.0003350149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001984109,"about_ca_topic_score_gemma":0.004127544,"domain_scores_codex":[0.9993852,0.00002632616,0.00002428719,0.0001394649,0.0003724266,0.0000521939],"domain_scores_gemma":[0.9995771,0.0001566066,0.00007341558,0.00005406113,0.0001212647,0.00001755181],"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":[0.00007747772,0.00002310485,0.0005294608,0.00003327061,0.000005611054,0.00003030722,0.00006183428,0.0001619688,0.9946346,0.0001434509,0.0001043207,0.004194656],"study_design_scores_gemma":[0.00001359373,0.00008804182,0.004057108,0.000003307419,0.000006431152,0.00005039373,0.00004366719,0.002406808,0.991473,0.00005757587,0.001792961,0.00000717607],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9283404,0.002248832,0.06293796,0.0001800757,0.00008431314,0.0001378848,0.001342658,0.0005743473,0.004153501],"genre_scores_gemma":[0.963338,0.001004171,0.02994616,0.00007213594,0.00001915741,0.0001066545,0.0009070259,0.0001104209,0.004496302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002105817,"threshold_uncertainty_score":0.007044733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009076412367827013,"score_gpt":0.2133112309158207,"score_spread":0.2042348185479937,"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."}}