{"id":"W2789553340","doi":"","title":"CHARACTERIZATION OF NANOPARTICLES EMITTED DURING DRY CUTTING","year":2014,"lang":"en","type":"article","venue":"","topic":"Nanotechnology research and applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Scanning mobility particle sizer; Nanoparticle; Characterization (materials science); Nanomaterials; Scanning electron microscope; Materials science; Particle (ecology); Nanotechnology; Machining; Process engineering; Spectrometer; Aluminium; Particle size; Particle-size distribution; Metallurgy; Composite material; Chemical engineering; Optics; Engineering; Physics","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":[0.0001750877,0.0002349225,0.0002024554,0.0005012041,0.0002243888,0.0002407999,0.0002256757,0.0003690564,0.0008659047],"category_scores_gemma":[0.0002352966,0.0001366951,0.0001906553,0.0002589942,0.0002048344,0.0002505004,0.0001478987,0.0003039211,0.0002524545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001593082,"about_ca_system_score_gemma":0.00009649323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005106246,"about_ca_topic_score_gemma":0.0009000074,"domain_scores_codex":[0.9997888,0.00001288453,0.000009936523,0.00005060964,0.0001121788,0.00002565948],"domain_scores_gemma":[0.9998159,0.00006024122,0.00003862663,0.00001247827,0.00006389734,0.000008979404],"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":[0.00002726701,0.000009266151,0.0003778129,0.00002974163,0.0000020535,0.0000393815,0.00004461389,0.00008708136,0.9972795,0.00002810472,0.00002936196,0.002045987],"study_design_scores_gemma":[0.000003552013,0.0001638466,0.006346111,0.000005202418,0.000005962781,0.0001350737,0.00007094758,0.001190438,0.9902503,0.00004893023,0.001771609,0.000007904277],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9788303,0.0009623813,0.01681151,0.00003763038,0.00002746646,0.0000614821,0.0004846099,0.0001301041,0.002654604],"genre_scores_gemma":[0.9725273,0.0007769017,0.01907086,0.0001257773,0.00001383071,0.0001084459,0.0009361558,0.00009049271,0.006350291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008659047,"threshold_uncertainty_score":0.002896726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004476354428415368,"score_gpt":0.1979350962458867,"score_spread":0.1934587418174714,"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."}}