{"id":"W4236500163","doi":"10.26434/chemrxiv.8038973.v2","title":"Controlling Thermal Stability and Volatility of Organogold(I) Compounds for Vapor Deposition with Complementary Ligand Design","year":2019,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Molecular Junctions and Nanostructures","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Volatility (finance); Thermogravimetric analysis; Thermal stability; Chemical vapor deposition; Density functional theory; Chemistry; Group 2 organometallic chemistry; Stability (learning theory); Thermal; Materials science; Computational chemistry; Physical chemistry; Thermodynamics; Organic chemistry; Mathematics; Molecule; Computer science; Physics; Econometrics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001936522,0.0002327664,0.0004049377,0.00004655385,0.00005168543,0.00003255746,0.00009756369,0.0001461442,0.00002409979],"category_scores_gemma":[0.00000932822,0.0002026243,0.00007243234,0.00004591681,0.00006373219,0.0000387034,0.00005846922,0.0001959808,1.812333e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005008193,"about_ca_system_score_gemma":0.00004047159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003227705,"about_ca_topic_score_gemma":0.00001403368,"domain_scores_codex":[0.999123,0.00002960746,0.0002874717,0.0002854571,0.0001110707,0.0001633354],"domain_scores_gemma":[0.9992915,0.0001129727,0.0000951608,0.0003492211,0.0001048381,0.00004627527],"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":[0.0006199997,0.00007057225,0.01988318,0.002990686,0.0006665374,0.000002018231,0.0004015173,0.02791357,0.9463045,0.00002940199,0.0002132167,0.0009047713],"study_design_scores_gemma":[0.00141099,0.0001149573,0.007830782,0.000112221,0.0001979428,0.000003975593,0.00003928111,0.1522237,0.8374375,0.0003121504,0.00003844643,0.0002779941],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7622998,0.0005458574,0.235937,0.00001065573,0.0001505581,0.0008869594,0.00004651619,0.00005431411,0.0000682879],"genre_scores_gemma":[0.9892439,0.00001691346,0.01043674,0.00001155254,0.00004755469,0.00004969951,0.0001542184,0.00003698763,0.000002464954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2269441,"threshold_uncertainty_score":0.8262779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0179139245705487,"score_gpt":0.2136832712673652,"score_spread":0.1957693466968165,"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."}}