{"id":"W4252188961","doi":"10.26434/chemrxiv.13190636.v1","title":"Hexacoordinated Gallium(III) Triazenide Precursor for Epitaxial Gallium Nitride by Atomic Layer Deposition","year":2020,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"GaN-based semiconductor devices and materials","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Supercomputer Centre, Linköpings Universitet; Knut och Alice Wallenbergs Stiftelse; Linköpings Universitet; National Science Council; Vetenskapsrådet; Stiftelsen för Strategisk Forskning","keywords":"Materials science; Epitaxy; Atomic layer deposition; Gallium nitride; Gallium; Chemical vapor deposition; Sublimation (psychology); Layer (electronics); Stoichiometry; Thin film; Substrate (aquarium); Optoelectronics; Analytical Chemistry (journal); Nanotechnology; Chemistry; Metallurgy; Physical chemistry","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":[0.00006431163,0.0002790097,0.0002012945,0.0001904564,0.00009673737,0.0001484449,0.0002682776,0.0001691222,0.0009167224],"category_scores_gemma":[0.00008790914,0.0002256686,0.0001875428,0.0001744823,0.00008295676,0.0001366213,0.0001897532,0.0003224402,0.0004763701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001463428,"about_ca_system_score_gemma":0.0001430072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003521096,"about_ca_topic_score_gemma":0.00114958,"domain_scores_codex":[0.9999369,0.000004808199,0.000005751741,0.00001724081,0.00002700147,0.000008268555],"domain_scores_gemma":[0.999961,0.000003831747,0.00001037707,0.000009174122,0.00001016543,0.000005489236],"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":[0.000006824831,0.000003409574,0.00007320679,0.00003749321,0.000002335459,0.00003231343,0.000007374033,0.00003563737,0.9986784,0.00004909873,0.00003499751,0.001038839],"study_design_scores_gemma":[0.000004501565,0.00006927169,0.0007244989,0.0000038673,0.000006350434,0.0002061036,0.000009641707,0.0007183894,0.9953412,0.00002006532,0.002892511,0.000003505899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9597725,0.00306542,0.03044583,0.0001023059,0.0001219546,0.0002175765,0.000530161,0.0005175907,0.00522673],"genre_scores_gemma":[0.9511672,0.002000295,0.04208128,0.0000446302,0.00001392071,0.00009486974,0.0005754797,0.0001077219,0.003914641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009167224,"threshold_uncertainty_score":0.003066719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0249316840840157,"score_gpt":0.2669388200325083,"score_spread":0.2420071359484926,"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."}}