{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001470333,0.0002057183,0.0002345138,0.0001757164,0.000226611,0.0003022225,0.000346607,0.0004661972,0.0009927526],"category_scores_gemma":[0.0002142654,0.0002082029,0.0002115938,0.0001576712,0.0001948837,0.0002403418,0.0002737123,0.0003992169,0.0003982251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000386059,"about_ca_system_score_gemma":0.000258777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003511948,"about_ca_topic_score_gemma":0.0009241918,"domain_scores_codex":[0.9998884,0.00001096541,0.000006935796,0.00002294905,0.00005491312,0.00001573314],"domain_scores_gemma":[0.9999347,0.00001819006,0.00001091155,0.000009845554,0.00001843933,0.000007860916],"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":[0.00001708198,0.000008349599,0.00001876522,0.00004729634,0.000002549674,0.0000228814,0.00001724129,0.0001001296,0.9974687,0.0001533463,0.00006986494,0.002073826],"study_design_scores_gemma":[0.000005796674,0.00004182148,0.0001203857,0.000001576724,0.000003469353,0.00003959691,0.000004625656,0.00113442,0.9974602,0.00004371049,0.0011419,0.000002429427],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9549802,0.002853665,0.03288568,0.0002833225,0.0001075752,0.00008547528,0.0001393696,0.000298829,0.008365981],"genre_scores_gemma":[0.9788714,0.0006983249,0.01520617,0.00005848586,0.00001558561,0.00004964094,0.00009109763,0.00005465172,0.004954534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009927526,"threshold_uncertainty_score":0.003321052,"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."}}