{"id":"W1968009784","doi":"10.3390/molecules170910119","title":"Dry Etching of Copper Phthalocyanine Thin Films: Effects on Morphology and Surface Stoichiometry","year":2012,"lang":"en","type":"article","venue":"Molecules","topic":"Copper-based nanomaterials and applications","field":"Materials Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Nanopillar; X-ray photoelectron spectroscopy; Materials science; Copper; Stoichiometry; Phthalocyanine; Thin film; Etching (microfabrication); Analytical Chemistry (journal); Argon; Copper phthalocyanine; Plasma etching; Chemical engineering; Nanotechnology; Chemistry; Nanostructure; Optoelectronics; Metallurgy; Physical chemistry; Organic 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001712045,0.000285799,0.00025574,0.0001510676,0.0001449214,0.0003103255,0.000264504,0.0002291601,0.0007001591],"category_scores_gemma":[0.000528558,0.0002817905,0.0001182731,0.0001862501,0.0002087141,0.0002153732,0.0001444008,0.0002611228,0.0001222835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002228793,"about_ca_system_score_gemma":0.0001155057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007663848,"about_ca_topic_score_gemma":0.000885699,"domain_scores_codex":[0.999843,0.00001559408,0.00001019833,0.00003426611,0.00006487415,0.00003205219],"domain_scores_gemma":[0.9996911,0.0001233943,0.00008644767,0.0000333838,0.00004830235,0.00001749519],"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":[0.00003144605,0.000004833215,0.0001487465,0.00002343668,0.000003243227,0.00003281174,0.00001760802,0.0000502541,0.9991527,0.00001135952,0.00001116577,0.0005125356],"study_design_scores_gemma":[0.000006977149,0.00007727173,0.002238646,0.000001492479,0.000005447045,0.00005987406,0.00001697564,0.0005720487,0.9966994,0.000008342864,0.0003108775,0.000002482854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984456,0.0003431572,0.0006582178,0.00002425729,0.000008305422,0.00000852409,0.00007362285,0.00002357278,0.0004147357],"genre_scores_gemma":[0.9957445,0.0005293439,0.002893813,0.0000179204,0.000006975013,0.00001914232,0.0001249196,0.00003663631,0.0006268056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007663848,"threshold_uncertainty_score":0.002342224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129176734522517,"score_gpt":0.2564149098631723,"score_spread":0.2451231425179471,"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."}}