{"id":"W4392759472","doi":"10.5194/egusphere-egu24-13392","title":"Investigating lignin’s ice nucleation mechanisms by applying nano-particle synthesis and high-speed cryo-microscopy","year":2024,"lang":"en","type":"preprint","venue":"","topic":"nanoparticles nucleation surface interactions","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Nucleation; Lignin; Nano-; Materials science; Particle (ecology); Nanotechnology; Chemical engineering; Biophysics; Chemistry; Composite material; Organic chemistry; Biology; Engineering","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":[0.000387827,0.0002711489,0.0001584719,0.0002422144,0.0002499059,0.0003540465,0.0004231137,0.0003188985,0.00148453],"category_scores_gemma":[0.0002593971,0.0001460331,0.0002263849,0.0001211388,0.0003159188,0.000410706,0.0001991448,0.0006083493,0.0003362108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007704232,"about_ca_system_score_gemma":0.0001653138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001278534,"about_ca_topic_score_gemma":0.001969066,"domain_scores_codex":[0.9998773,0.00001107533,0.000006507159,0.00003688269,0.00004780948,0.00002036271],"domain_scores_gemma":[0.9998228,0.00006005195,0.00003590143,0.00002910493,0.00003968669,0.00001246032],"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":[0.00001844423,0.00002211257,0.0002076568,0.00008021412,0.00000531827,0.00004114588,0.00003643251,0.0005393762,0.9948103,0.0008099477,0.0001178895,0.003311065],"study_design_scores_gemma":[0.000003559572,0.00004497158,0.001094333,0.000006795951,0.000003155908,0.00003888193,0.00001310239,0.004149378,0.9920768,0.0001262967,0.002437474,0.000005317675],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8476647,0.005273484,0.1316312,0.0003048176,0.0001691125,0.0003300033,0.001316441,0.0003385311,0.01297164],"genre_scores_gemma":[0.869359,0.00277554,0.1222802,0.0001267822,0.00004858909,0.0002288211,0.0007306653,0.0001420909,0.004308423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00148453,"threshold_uncertainty_score":0.005589843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02403654850084004,"score_gpt":0.2562753197574127,"score_spread":0.2322387712565727,"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."}}