{"id":"W2317312454","doi":"10.1021/om049238c","title":"Ferrocenyl-Passivated Nanoclusters:  Synthesis of [Cu<sub>20</sub>Se<sub>6</sub>(Se<sub>2</sub>fc)<sub>4</sub>(PR<sub>2</sub>R‘)<sub>10</sub>] and [Cu<sub>40</sub>Se<sub>12</sub>(Se<sub>2</sub>fc)<sub>8</sub>(PPh<sub>3</sub>)<sub>9</sub>]","year":2005,"lang":"en","type":"article","venue":"Organometallics","topic":"Nanocluster Synthesis and Applications","field":"Materials Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanoclusters; Chemistry; Crystallography; Reagent; Inorganic chemistry; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","metaepi_broad","bibliometrics","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","metaepi_broad","bibliometrics","sts","scholarly_communication","open_science","research_integrity"],"category_scores_codex":[0.01624052,0.02258376,0.02248273,0.01342214,0.01165407,0.009447386,0.01938957,0.01411086,0.0006392753],"category_scores_gemma":[0.008272588,0.02510057,0.01108065,0.02477542,0.01210728,0.01450596,0.01264061,0.01363974,0.01987888],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01079509,"about_ca_system_score_gemma":0.009028658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003892244,"about_ca_topic_score_gemma":0.007148765,"domain_scores_codex":[0.9023518,0.008684923,0.02398244,0.02447023,0.0170931,0.02341748],"domain_scores_gemma":[0.9276885,0.009973866,0.01864764,0.02129527,0.008765638,0.01362912],"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":[0.005106428,0.01015574,0.0009829107,0.004716306,0.005382814,0.001602826,0.004278337,0.002149802,0.8564323,0.0008440485,0.02642501,0.08192348],"study_design_scores_gemma":[0.01696522,0.003359635,0.00466737,0.005853661,0.009549124,0.002866311,0.0027679,0.00369135,0.9158289,0.002260629,0.008131016,0.02405883],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9313051,0.008457939,0.005,0.005752978,0.009132105,0.01895869,0.01153158,0.008144253,0.00171736],"genre_scores_gemma":[0.9245926,0.03543972,0.001677879,0.005272386,0.008881683,0.00926819,0.006637453,0.008036248,0.0001938381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05939665,"threshold_uncertainty_score":0.9992777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01891773986589556,"score_gpt":0.2326305748428184,"score_spread":0.2137128349769228,"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."}}