{"id":"W3204883845","doi":"10.3390/chemistry3040083","title":"Partitioning Hückel–London Currents into Cycle Contributions","year":2021,"lang":"en","type":"article","venue":"Chemistry","topic":"Synthesis and Properties of Aromatic Compounds","field":"Chemistry","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Current (fluid); Representation (politics); Graph; Ring (chemistry); Electronic circuit; Statistical physics; Graph theory; Conjugated system; Aromaticity; Basis (linear algebra); Hückel method; Ab initio; Algorithm; Computer science; Computational chemistry; Theoretical physics; Mathematics; Physics; Chemistry; Theoretical computer science; Thermodynamics; Molecule; Quantum mechanics; Combinatorics; Geometry; Organic chemistry; Nuclear magnetic resonance","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006977573,0.0001475753,0.0001898485,0.000006047653,0.0002365842,0.00009466223,0.0001844388,0.0001144859,0.008788215],"category_scores_gemma":[0.000393743,0.0001528241,0.0001203055,0.00008175681,0.00006726616,0.000077371,0.0001208719,0.0001814439,0.0001172175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001047351,"about_ca_system_score_gemma":0.0001115617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001627499,"about_ca_topic_score_gemma":0.0000018465,"domain_scores_codex":[0.9990004,0.000009531866,0.0002596735,0.0002810243,0.0001906889,0.000258623],"domain_scores_gemma":[0.9991252,0.00009255585,0.00007340091,0.0004442517,0.000135492,0.0001291187],"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":[0.000009423519,0.0001481066,0.002084977,0.0003174382,0.00005997255,0.00002614028,0.0001561672,0.00001499039,0.9858731,0.00004407047,0.004062626,0.007202967],"study_design_scores_gemma":[0.0003467129,0.000001588236,0.0000691719,0.0001946814,0.00002825762,0.00003517972,0.0002747662,0.0003519397,0.9487595,0.00153892,0.04820189,0.0001973739],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9111571,0.001940542,0.00006565181,0.0005977408,0.0001001681,0.00001580508,0.00003463001,0.0001302073,0.08595817],"genre_scores_gemma":[0.9961161,0.0000658774,0.0002943173,0.00005395577,0.0002786459,0.00003163976,0.000193819,0.00001758066,0.002948061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08495902,"threshold_uncertainty_score":0.9921179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009284902293260629,"score_gpt":0.2438733341075753,"score_spread":0.2345884318143146,"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."}}