{"id":"W2081578007","doi":"10.1021/jp049300j","title":"Distances in Molecular Graphs","year":2004,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry A","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Vertex (graph theory); Chemistry; Molecular graph; Molecule; Numbering; Equivalence (formal languages); Computational chemistry; Graph; Theoretical physics; Combinatorics; Physics; Computer science; Algorithm; Pure mathematics; Mathematics","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":[0.001179635,0.0008650594,0.0007252621,0.004112239,0.001842724,0.003166765,0.001198917,0.001442793,0.006375684],"category_scores_gemma":[0.005876479,0.0004769251,0.0009241831,0.004180197,0.003192371,0.008788309,0.002270405,0.00236926,0.001782341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001713942,"about_ca_system_score_gemma":0.0004379546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001373496,"about_ca_topic_score_gemma":0.000979438,"domain_scores_codex":[0.9983042,0.0004861804,0.0001349392,0.0003947563,0.0005341119,0.0001456881],"domain_scores_gemma":[0.9968363,0.002018655,0.0003541971,0.0002679551,0.0003619696,0.0001608403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009273376,0.000006971252,0.0001456505,0.0001273005,0.000009352769,0.00004592246,0.0001783166,0.002990344,0.0003238701,0.9750357,0.00163302,0.01949438],"study_design_scores_gemma":[0.000003814009,0.00001675039,0.000139707,0.00004701099,0.000008371631,0.0001424335,0.00007951105,0.00419696,0.0003357017,0.9580764,0.03693962,0.00001374214],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04767762,0.05182631,0.7580969,0.004913943,0.002043051,0.0001934427,0.001199401,0.000578539,0.1334707],"genre_scores_gemma":[0.5298185,0.03921638,0.3898887,0.001673769,0.002788344,0.0003448972,0.001672904,0.0005643463,0.03403215],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006375684,"threshold_uncertainty_score":0.02132875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006090147825353131,"score_gpt":0.2435981851755624,"score_spread":0.2375080373502093,"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."}}