{"id":"W2785057641","doi":"10.37236/3797","title":"A Large Set of Torus Obstructions and How They Were Discovered","year":2018,"lang":"en","type":"article","venue":"The Electronic Journal of Combinatorics","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Torus; Embedding; Mathematics; Set (abstract data type); Planar graph; Graph; Book embedding; Quadratic equation; Graph embedding; Combinatorics; Discrete mathematics; Algorithm; Theoretical computer science; 1-planar graph; Computer science; Chordal graph; Artificial intelligence; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.0004139702,0.00009566119,0.0001785659,0.00005090791,0.0001201327,0.0001098925,0.0006738962,0.00003316138,0.000001600168],"category_scores_gemma":[0.00004191777,0.00005933829,0.00007742835,0.0002340603,0.0001086588,0.0005118898,0.000163428,0.0002550258,0.000001515182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006490965,"about_ca_system_score_gemma":0.0002211058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002868566,"about_ca_topic_score_gemma":0.00001271471,"domain_scores_codex":[0.9990559,0.00004860493,0.0001800383,0.00008817117,0.0002954802,0.0003318178],"domain_scores_gemma":[0.9990776,0.00006941627,0.0002880377,0.0002769871,0.0002301029,0.00005791981],"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":[0.00001060494,0.00003607164,0.0001609007,0.000003465146,0.00004840631,0.000001704951,0.0007090109,0.000001248355,0.00007768379,0.9967092,0.0005700442,0.00167166],"study_design_scores_gemma":[0.0005540861,0.0008680538,0.0005367675,0.00001796122,0.00002393257,0.0002918121,0.0002560272,0.0002810587,0.001489193,0.9841868,0.01140665,0.00008768093],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9339454,0.001808558,0.05659018,0.004247819,0.001136847,0.00009368069,0.000008976414,0.00001817084,0.002150429],"genre_scores_gemma":[0.9993277,0.0001804156,0.00003703402,0.00003813899,0.0001003813,2.869621e-7,3.37216e-7,0.000005873359,0.0003098575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06538234,"threshold_uncertainty_score":0.2419745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007030571926645761,"score_gpt":0.2144578355214902,"score_spread":0.2074272635948445,"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."}}