{"id":"W2484039598","doi":"10.1016/j.jcis.2016.07.050","title":"Pulsed laser ablation based synthesis of colloidal metal nanoparticles for catalytic applications","year":2016,"lang":"en","type":"article","venue":"Journal of Colloid and Interface Science","topic":"Laser-Ablation Synthesis of Nanoparticles","field":"Engineering","cited_by":248,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Catalysis; Nanoparticle; Nanotechnology; Colloid; Metal; Laser ablation synthesis in solution; Materials science; Laser ablation; Chemical engineering; Chemistry; Organic chemistry; Laser","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007673125,0.00009327389,0.0002115307,0.0002100369,0.00008489337,0.00004630632,0.0002361939,0.00002988802,0.00002260419],"category_scores_gemma":[0.000453097,0.00006333812,0.00006441241,0.0003466084,0.0002754318,0.0006726044,0.00001858205,0.00003233373,0.000004526674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007564735,"about_ca_system_score_gemma":0.000119304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001041228,"about_ca_topic_score_gemma":0.000003258318,"domain_scores_codex":[0.9989588,0.00001693191,0.0004412986,0.0001142815,0.0002907516,0.0001779605],"domain_scores_gemma":[0.9986918,0.0005398738,0.000194617,0.0001337033,0.0003274523,0.0001125304],"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":[0.00003957495,0.00003458985,0.0003224046,0.00002474971,0.00001644604,5.660883e-8,0.00003233004,0.003544874,0.9922906,0.00006380723,0.00009025705,0.003540366],"study_design_scores_gemma":[0.0004023793,0.00009079083,0.001151323,0.00008569908,0.00004315487,0.000005837245,0.00005966059,0.006920111,0.9900073,0.000140819,0.001007474,0.00008545006],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738766,0.0001083486,0.02518616,0.0003513457,0.00009708502,0.0002066719,0.00002486935,0.00001929506,0.0001296043],"genre_scores_gemma":[0.9972197,0.00001772465,0.002638218,0.00001001619,0.00002848666,0.00002447871,7.230737e-8,0.00001032119,0.00005092989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02334314,"threshold_uncertainty_score":0.2582854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01100349375164042,"score_gpt":0.2417178058565358,"score_spread":0.2307143121048954,"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."}}