{"id":"W4387607386","doi":"10.26434/chemrxiv-2023-sspnq-v3","title":"Mechanistic study of the atomic layer deposition of cobalt: A combined mass spectrometric and computational approach","year":2023,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Semiconductor materials and devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Western Canada Research Grid; Compute Canada","keywords":"Alkyne; Atomic layer deposition; Cobalt; Chemistry; Deposition (geology); Mass spectrometry; Electrospray ionization; Layer (electronics); Surface modification; Reactivity (psychology); Analytical Chemistry (journal); Inorganic chemistry; Physical chemistry; Catalysis; Organic chemistry; Chromatography","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":[0.000407361,0.0006049798,0.0005977203,0.0004199084,0.0004775649,0.0008971774,0.00146784,0.0009312725,0.002364164],"category_scores_gemma":[0.0004912012,0.0003772631,0.0006606026,0.000398238,0.000373487,0.0007768384,0.0004325129,0.0008061596,0.0002609155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008089785,"about_ca_system_score_gemma":0.001239759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003039245,"about_ca_topic_score_gemma":0.003187552,"domain_scores_codex":[0.9998909,0.00001585634,0.000004449639,0.00001652642,0.00004470142,0.0000275305],"domain_scores_gemma":[0.9998555,0.00006074471,0.00002437456,0.00001842641,0.00002903162,0.00001193196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004276333,0.0005363025,0.004222148,0.001905719,0.0002848012,0.001226741,0.0001837378,0.8059175,0.1279584,0.04248511,0.001413546,0.01343837],"study_design_scores_gemma":[0.00007693506,0.0001248162,0.0009013472,0.00002793736,0.00005594514,0.000118429,0.00007534159,0.9660169,0.02620767,0.004443203,0.001930408,0.00002102208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9097414,0.001897627,0.0491422,0.001333903,0.0001368509,0.0002879501,0.002854632,0.0003306538,0.03427472],"genre_scores_gemma":[0.9681329,0.001747753,0.02715775,0.000138713,0.00001950568,0.0002314958,0.0006799161,0.00004057737,0.001851402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003039245,"threshold_uncertainty_score":0.007908881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03310886687677845,"score_gpt":0.2376528348436275,"score_spread":0.2045439679668491,"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."}}