{"id":"W4390545031","doi":"10.3390/coatings14010068","title":"Effect of Carbon-Doped Cu(Ni) Alloy Film for Barrierless Copper Interconnect","year":2024,"lang":"en","type":"article","venue":"Coatings","topic":"Copper Interconnects and Reliability","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Government of Jiangsu Province; China Postdoctoral Science Foundation; Jiangsu Science and Technology Department; National Natural Science Foundation of China","keywords":"Materials science; Diffusion barrier; Alloy; Silicon; Sputter deposition; Substrate (aquarium); Doping; Analytical Chemistry (journal); Copper; Layer (electronics); Barrier layer; Photoemission spectroscopy; Diffusion; Carbon fibers; Metallurgy; X-ray photoelectron spectroscopy; Sputtering; Chemical engineering; Thin film; Composite material; Nanotechnology; Optoelectronics; Chemistry; Composite number","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":[0.00005267417,0.0003355925,0.0001850863,0.0001996829,0.0001839715,0.0002648058,0.0002515631,0.0002574049,0.0007613273],"category_scores_gemma":[0.0001995673,0.0001627195,0.0001094103,0.0002005224,0.00008548726,0.0002559088,0.0001074105,0.0001816116,0.000147436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002168643,"about_ca_system_score_gemma":0.0001374099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001508643,"about_ca_topic_score_gemma":0.003964473,"domain_scores_codex":[0.9999349,0.000005931865,0.000004612082,0.0000149424,0.00002362655,0.00001596903],"domain_scores_gemma":[0.9998746,0.00001931256,0.00002611424,0.000008924701,0.00004847131,0.00002259478],"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":[0.00006432374,0.00001265324,0.0001464728,0.00009556945,0.000007569108,0.00009449973,0.00001483877,0.00007460431,0.9981268,0.00002575442,0.00005636034,0.001280511],"study_design_scores_gemma":[0.000005823728,0.0001498131,0.001104124,0.000006793827,0.00001932301,0.00008717214,0.00002137521,0.0006602001,0.9969681,0.00000504068,0.0009687655,0.000003473973],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945403,0.003148198,0.0006482365,0.0000572716,0.00006125419,0.00001330587,0.00006463245,0.00005297965,0.001413776],"genre_scores_gemma":[0.9962348,0.001154964,0.001489428,0.00002754702,0.00001070637,0.000007528078,0.00005798015,0.00001669212,0.001000267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001508643,"threshold_uncertainty_score":0.002999723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01080576620591607,"score_gpt":0.2803619920229363,"score_spread":0.2695562258170203,"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."}}