{"id":"W2953166580","doi":"10.1101/463505","title":"Nanoscale fracture of defective popgraphene monolayer","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Graphene research and applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Université du Québec à Montréal; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; McGill University","keywords":"Materials science; Nanodevice; Crystallographic defect; Nanoscopic scale; Fracture (geology); Brittleness; Fracture mechanics; Brittle fracture; Monolayer; Composite material; Nanotechnology; Condensed matter physics; Physics","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":[0.00005532608,0.0001455329,0.0001762857,0.0001672002,0.0002635525,0.0002697102,0.0002972712,0.0004001462,0.001534657],"category_scores_gemma":[0.0001493951,0.0001133431,0.0001981904,0.0001170856,0.0002542701,0.0002339093,0.0001923071,0.0003365996,0.0001077315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000462554,"about_ca_system_score_gemma":0.000181179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002233816,"about_ca_topic_score_gemma":0.002275039,"domain_scores_codex":[0.999935,0.000002644201,0.000001827251,0.00001064083,0.00002921304,0.00002068321],"domain_scores_gemma":[0.9999543,0.00001343382,0.00000759094,0.00000860978,0.000007199676,0.000008815929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001627566,0.00006055917,0.002885545,0.0001168841,0.00003970765,0.0007423729,0.0001109293,0.04040253,0.9491258,0.002129337,0.0002879731,0.00393562],"study_design_scores_gemma":[0.00002821175,0.0003647867,0.01352853,0.00002164863,0.0000215717,0.0002098062,0.0001963744,0.298908,0.6840035,0.001089205,0.00158874,0.00003963966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988118,0.00005854623,0.0005647022,0.00001902646,0.000004171876,0.000001937643,0.0000824899,0.00001725768,0.0004399348],"genre_scores_gemma":[0.9992701,0.00005102832,0.000289683,0.000006969289,7.940265e-7,0.000002536099,0.00007252331,0.000005749831,0.0003005239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002233816,"threshold_uncertainty_score":0.005133986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01371751750166698,"score_gpt":0.2454052432750626,"score_spread":0.2316877257733957,"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."}}