{"id":"W2918744402","doi":"","title":"Iterative algorithm for computing irregularity strength of complete graph.","year":2018,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Graph Labeling and Dimension Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Algorithm; Graph; Combinatorics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001203346,0.0006535258,0.0008894827,0.001964258,0.0007525818,0.001269657,0.002042988,0.001026142,0.00766268],"category_scores_gemma":[0.007375263,0.0004325727,0.0008199536,0.001523307,0.0008904451,0.00179095,0.002208703,0.001405904,0.001927289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009302784,"about_ca_system_score_gemma":0.001947168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003203322,"about_ca_topic_score_gemma":0.006232142,"domain_scores_codex":[0.9991647,0.0002635196,0.00005014742,0.0001640483,0.0002448723,0.000112688],"domain_scores_gemma":[0.9970295,0.001218807,0.0001818971,0.0006161705,0.0007731094,0.000180454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008198346,0.0003815713,0.006613153,0.0006026012,0.0002519026,0.0002096601,0.0005559391,0.1853619,0.01667742,0.1784324,0.02454016,0.5855534],"study_design_scores_gemma":[0.00009742491,0.0001288318,0.001137874,0.00003726828,0.00004567546,0.000145215,0.0001278952,0.8679311,0.005355821,0.1194877,0.005473769,0.0000313916],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02233631,0.0001822594,0.9710422,0.0001700383,0.00007873373,0.0001205487,0.0002548072,0.001159761,0.004655355],"genre_scores_gemma":[0.1808376,0.0001254966,0.8132262,0.00009643198,0.0000509183,0.0003157595,0.0009603992,0.0002554637,0.004131672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00766268,"threshold_uncertainty_score":0.02563423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01930189634969985,"score_gpt":0.2559862754358235,"score_spread":0.2366843790861236,"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."}}