{"id":"W2069890507","doi":"10.1016/j.ijhydene.2008.06.058","title":"Thermal and catalytic dry reforming and cracking of ethanol for hydrogen and carbon nanofilaments' production","year":2008,"lang":"en","type":"article","venue":"International Journal of Hydrogen Energy","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":83,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cracking; Catalysis; Carbon fibers; Fluid catalytic cracking; Hydrogen; Chemical engineering; Ethanol; Carbon dioxide reforming; Materials science; Hydrogen production; Chemistry; Syngas; Organic chemistry; Composite material; Composite number","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001276918,0.0001820096,0.0002434289,0.000211589,0.0002626434,0.0001876925,0.0002436632,0.0001974752,0.001676285],"category_scores_gemma":[0.0002001987,0.000138156,0.0002325624,0.000126749,0.0002077153,0.000350207,0.0001916304,0.0003478019,0.0001997183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002978565,"about_ca_system_score_gemma":0.0001931391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001532394,"about_ca_topic_score_gemma":0.004666276,"domain_scores_codex":[0.9999167,0.000005217344,0.000004519301,0.00001170325,0.00003590771,0.00002602177],"domain_scores_gemma":[0.9999615,0.000008605892,0.000007723223,0.000006049703,0.00001010458,0.000005930925],"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":[0.000219513,0.00002958918,0.0002695761,0.0001302104,0.00000946549,0.00003940931,0.00004590836,0.0004107408,0.9922404,0.0003311586,0.0001548107,0.006119122],"study_design_scores_gemma":[0.000006042991,0.00007291378,0.001317594,0.000001926634,0.000004316405,0.00002396333,0.00001427764,0.0009720668,0.9968814,0.00001785485,0.0006838624,0.000003816184],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960172,0.0007072278,0.001289525,0.00004664637,0.00001892343,0.00001601826,0.0001063657,0.00002787197,0.001770367],"genre_scores_gemma":[0.9972124,0.0001853374,0.0008392761,0.000009326983,0.000004276692,0.000006327851,0.0000788713,0.00001042342,0.00165379],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001676285,"threshold_uncertainty_score":0.005607724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01228913714965806,"score_gpt":0.2395864186905733,"score_spread":0.2272972815409153,"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."}}