{"id":"W2009484617","doi":"10.1063/1.2937249","title":"Modeling self-annealing kinetics in electroplated Cu thin films","year":2008,"lang":"en","type":"article","venue":"Journal of Applied Physics","topic":"Copper Interconnects and Reliability","field":"Materials Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Allianz Industrie Forschung","keywords":"Electroplating; Annealing (glass); Materials science; Kinetics; Electrolyte; Recrystallization (geology); Thin film; Microstructure; Copper; Metallurgy; Composite material; Electrode; Nanotechnology; Chemistry; Physical chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003650338,0.0001354739,0.0003148789,0.00005132471,0.00007119438,0.00003139643,0.0002466849,0.00007329875,0.00004661135],"category_scores_gemma":[0.00001719521,0.0001058189,0.00008906914,0.0001903439,0.00003489067,0.0001240946,0.00003576277,0.0003588069,0.00001818874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008565165,"about_ca_system_score_gemma":0.0001021307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002539571,"about_ca_topic_score_gemma":0.000004344522,"domain_scores_codex":[0.9986936,0.00002657946,0.0005594294,0.0001548628,0.0003070309,0.000258485],"domain_scores_gemma":[0.9993432,0.00005584092,0.0002096958,0.0001666424,0.0001509763,0.00007360907],"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":[0.0000776489,0.0001459842,0.00003235721,0.00001235172,0.000008086926,0.00001722927,0.001218669,0.4517642,0.5462868,0.0002390465,0.000113299,0.00008432676],"study_design_scores_gemma":[0.0008652793,0.0001871871,0.00009423421,0.00005456002,0.00002777325,0.00008354539,0.0002195849,0.5540722,0.438116,0.005952789,0.00009516782,0.0002317053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959792,0.00006617676,0.002426992,0.00003104642,0.0002469767,0.00008704689,0.000001952196,0.00002531658,0.001135304],"genre_scores_gemma":[0.9940208,0.00007542235,0.005546588,0.00009405475,0.0002387752,0.000001451881,9.453923e-7,0.00001623218,0.000005746002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1081708,"threshold_uncertainty_score":0.4315169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01680745142901584,"score_gpt":0.2375673745109718,"score_spread":0.220759923081956,"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."}}