{"id":"W4367053597","doi":"10.2533/chimia.2023.256","title":"Nanoparticles Are Everywhere, Even Inside Trees","year":2023,"lang":"en","type":"article","venue":"CHIMIA International Journal for Chemistry","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Nanoparticle; Nanotechnology; Tree (set theory); Materials science; Mathematics; Combinatorics","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":[0.001888199,0.001224711,0.0005809909,0.001432776,0.002468146,0.004632074,0.0005790129,0.002571127,0.01731713],"category_scores_gemma":[0.001030733,0.0003030786,0.0005689142,0.001225779,0.002301763,0.003549732,0.002936362,0.002226758,0.004726402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003097293,"about_ca_system_score_gemma":0.004609495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009308741,"about_ca_topic_score_gemma":0.0158322,"domain_scores_codex":[0.9988748,0.0001721879,0.00003988769,0.0002117344,0.0003612721,0.0003399986],"domain_scores_gemma":[0.9988849,0.0002380561,0.00009607994,0.00005618791,0.0003105512,0.0004142746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001410254,0.0002655468,0.003999999,0.00277428,0.00007266856,0.001932149,0.00288065,0.0009782715,0.0734583,0.1360758,0.3043733,0.4717788],"study_design_scores_gemma":[0.00002144827,0.0001951933,0.005472946,0.0003586226,0.00001708151,0.0003508487,0.001354581,0.0001809071,0.006842745,0.007610776,0.9775611,0.00003378875],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.05991078,0.4035326,0.007325471,0.2020037,0.02676591,0.0001901487,0.001120038,0.0008355151,0.2983158],"genre_scores_gemma":[0.4001293,0.2067956,0.007542416,0.0178996,0.01582161,0.0001663203,0.00133188,0.0005091804,0.3498042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01731713,"threshold_uncertainty_score":0.05793154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02886646448170417,"score_gpt":0.3002056767966814,"score_spread":0.2713392123149772,"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."}}