{"id":"W4400237029","doi":"10.11159/tann24","title":"Proceedings of the 8th International Conference on Theoretical and Applied Nanoscience and Nanotechnology (TANN 2024)","year":2024,"lang":"en","type":"paratext","venue":"Proceedings of the International Conference of Theoretical and Applied Nanoscience and Nanotechnology","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanotechnology; Materials science; Engineering physics; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00192211,0.0009881735,0.001117876,0.001772606,0.0008642821,0.005420125,0.001133205,0.00156287,0.2958167],"category_scores_gemma":[0.002903348,0.000311968,0.0006337756,0.00143046,0.0005889062,0.00286906,0.00269669,0.002370076,0.1669226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009035751,"about_ca_system_score_gemma":0.001884325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001552682,"about_ca_topic_score_gemma":0.004239392,"domain_scores_codex":[0.9988224,0.0002419233,0.00005710777,0.0001320554,0.0005903959,0.0001560834],"domain_scores_gemma":[0.9973308,0.0003632595,0.0001017189,0.0002862474,0.00107576,0.0008422126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001170399,0.00009706774,0.0002422452,0.0002418378,0.00001939336,0.00006768444,0.00003636927,0.0004314955,0.001713372,0.006403945,0.8476071,0.1430225],"study_design_scores_gemma":[0.0000109463,0.00004700971,0.0005280421,0.0001054264,0.00001376355,0.0001149774,0.0000335635,0.001137642,0.000911304,0.003270938,0.9938177,0.000008647576],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.005792016,0.02496452,0.05452651,0.01673844,0.1291496,0.0004249777,0.007169746,0.003040877,0.7581933],"genre_scores_gemma":[0.008138425,0.006826311,0.008469271,0.001109378,0.005515114,0.0001361722,0.004721348,0.000815507,0.9642686],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2958167,"threshold_uncertainty_score":0.9896053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01091821557449968,"score_gpt":0.2526012945776477,"score_spread":0.241683079003148,"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."}}