{"id":"W4378469099","doi":"10.1002/advs.202301243","title":"In Situ Exfoliation Method of Large‐Area 2D Materials","year":2023,"lang":"en","type":"article","venue":"Advanced Science","topic":"Graphene research and applications","field":"Materials Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"China Scholarship Council; Vetenskapsrådet; Danmarks Frie Forskningsfond; Villum Fonden; Göran Gustafssons Stiftelser; Göran Gustafssons Stiftelse för Naturvetenskaplig och Medicinsk Forskning; Magnus Bergvalls Stiftelse; Gordon and Betty Moore Foundation; International Centre for Advanced Materials","keywords":"Exfoliation joint; Materials science; Photoemission spectroscopy; Electron diffraction; Ultra-high vacuum; Nanotechnology; Crystallinity; Low-energy electron diffraction; Substrate (aquarium); X-ray photoelectron spectroscopy; Diffraction; Chemical engineering; Composite material; Optics; Graphene","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":[0.0001023757,0.0002933547,0.0001970078,0.0002173243,0.0001684397,0.0002255522,0.0003094306,0.0002395729,0.001116038],"category_scores_gemma":[0.0001800283,0.0001649591,0.0001590206,0.0001289073,0.0001452143,0.0002783148,0.0002387374,0.0004417422,0.0002937381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001483686,"about_ca_system_score_gemma":0.00007447509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001110677,"about_ca_topic_score_gemma":0.0004392486,"domain_scores_codex":[0.9998918,0.00001143676,0.000008812082,0.00002957055,0.00004231631,0.00001605148],"domain_scores_gemma":[0.9998975,0.00003196876,0.00002440926,0.00002573872,0.00001212221,0.000008243309],"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":[0.00001333314,0.000008754664,0.00006339935,0.00007095443,0.000004132635,0.00007396608,0.00001938018,0.0001092743,0.9956073,0.0003187553,0.00009646719,0.003614327],"study_design_scores_gemma":[0.000001783494,0.0000182867,0.0001310893,0.000001894301,0.000002027601,0.0000888582,0.000006331116,0.0004652046,0.9971219,0.00003765293,0.002122671,0.000002230634],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8572434,0.00449765,0.1243628,0.0003253699,0.0004738849,0.0001580026,0.001226036,0.0007686546,0.01094416],"genre_scores_gemma":[0.9445581,0.0011185,0.05069243,0.00006744479,0.00002875093,0.00005856531,0.000378337,0.00006150313,0.003036353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001116038,"threshold_uncertainty_score":0.003733516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03161434111236308,"score_gpt":0.3984550411582512,"score_spread":0.3668407000458881,"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."}}