{"id":"W2126548818","doi":"10.1039/c5tc00143a","title":"Establishing the most favorable metal–carbon bond strength for carbon nanotube catalysts","year":2015,"lang":"en","type":"article","venue":"Journal of Materials Chemistry C","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Malting (Canada)","funders":"Irish Centre for High-End Computing; Vetenskapsrådet; Royal Society of Chemistry; Kempestiftelserna; Royal Society","keywords":"Materials science; Carbon nanotube; Catalysis; Carbon fibers; Carbon nanotube metal matrix composites; Metal; Bond strength; Bond; Nanotechnology; Chemical engineering; Composite material; Nanotube; Metallurgy; Composite number; Organic chemistry; Business","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":[0.003179183,0.0003292081,0.0007134736,0.00005882785,0.0001151807,0.0006019818,0.001109157,0.000181208,0.00006099418],"category_scores_gemma":[0.001720668,0.0002304167,0.0001477042,0.0002143706,0.0001530087,0.0003714921,0.0002541534,0.000198647,0.000003546879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002597145,"about_ca_system_score_gemma":0.0004792824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002073484,"about_ca_topic_score_gemma":0.000005447095,"domain_scores_codex":[0.9971409,0.0001155655,0.001115848,0.0003213946,0.0008004288,0.0005058668],"domain_scores_gemma":[0.9968879,0.0005001612,0.00111351,0.0006135303,0.0006367773,0.0002481111],"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":[0.0002810306,0.00007563989,0.00003823778,0.0001222496,0.00004690905,0.00002694457,0.000278101,0.0001058882,0.9960021,0.00001608203,0.002969786,0.0000370124],"study_design_scores_gemma":[0.001102764,0.0000985796,0.000006503341,0.0001215736,0.0001735758,0.0003399194,0.0003645556,0.00006027483,0.9936216,0.0004976651,0.003348977,0.0002639832],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933353,0.0007995071,0.000009470985,0.000488733,0.002880704,0.0002231681,0.00009733703,0.00004204108,0.002123749],"genre_scores_gemma":[0.9962245,0.00002054917,0.001412463,0.00006408749,0.001822761,0.00002154637,0.00001764028,0.0000538118,0.0003626705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002889179,"threshold_uncertainty_score":0.9396119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01883062068004598,"score_gpt":0.2505121678823488,"score_spread":0.2316815472023028,"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."}}