{"id":"W2079381308","doi":"10.1557/jmr.2010.0262","title":"Production of granulated-copper oxide nanoparticles for catalytic application","year":2010,"lang":"en","type":"article","venue":"Journal of materials research/Pratt's guide to venture capital sources","topic":"Copper-based nanomaterials and applications","field":"Materials Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Sharif University of Technology; U.S. Department of Energy","keywords":"Materials science; Chemical engineering; Nucleation; Supercritical fluid; Nanoparticle; Scanning electron microscope; Porosity; Particle (ecology); Transmission electron microscopy; Calcination; Copper oxide; Particle size; Copper; Catalysis; Nanotechnology; Composite material; Metallurgy; Thermodynamics; Organic chemistry","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":[0.00613727,0.0002412799,0.0005696225,0.0003577238,0.0003311133,0.0003013081,0.0007695161,0.0001787013,0.0002377724],"category_scores_gemma":[0.001483264,0.000189943,0.0001487564,0.0003787763,0.0003098206,0.0004215086,0.0001592005,0.0002182602,0.0001244398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008634721,"about_ca_system_score_gemma":0.0002334044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000205272,"about_ca_topic_score_gemma":0.00006771003,"domain_scores_codex":[0.9964928,0.0002768885,0.001372634,0.0004281181,0.0008672834,0.0005622753],"domain_scores_gemma":[0.9965695,0.0002985852,0.0007827147,0.0005819696,0.001470961,0.0002962885],"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":[0.0006072196,0.0002362137,0.00005533673,0.0001534302,0.00002057825,0.000002828207,0.0004961347,0.000240343,0.9886231,0.000681798,0.008400667,0.0004823222],"study_design_scores_gemma":[0.0004682138,0.0004061484,0.001064255,0.00009304871,0.00004430999,0.00007166119,0.0003913227,0.000006542916,0.9739996,0.001120145,0.02214332,0.0001914127],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938469,0.0002005782,0.0001591214,0.003111798,0.001241649,0.001218353,0.0001638127,0.00003574825,0.00002202795],"genre_scores_gemma":[0.9953227,0.00003049949,0.003093083,0.00004598937,0.001072499,0.0002025149,0.00002453662,0.00004824438,0.0001599478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01462351,"threshold_uncertainty_score":0.774565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02151919348095281,"score_gpt":0.3288603826490722,"score_spread":0.3073411891681194,"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."}}