{"id":"W6906380410","doi":"10.17605/osf.io/xney5","title":"Graph EquiJoin Dataset","year":2020,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Graph; Identification (biology); Graph theory; Field (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001415454,0.000374712,0.0004045909,0.0001212107,0.0002195162,0.0002518897,0.004465776,0.0001632886,0.0861894],"category_scores_gemma":[0.001495645,0.0004093586,0.0001980019,0.0009344767,0.0001333795,0.001160049,0.005330667,0.0006761021,0.6937334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006118287,"about_ca_system_score_gemma":0.00007930689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003201823,"about_ca_topic_score_gemma":0.000009140704,"domain_scores_codex":[0.9947012,0.0004290971,0.0005778024,0.003058721,0.0005497449,0.0006834441],"domain_scores_gemma":[0.9933311,0.0004711791,0.0002548122,0.005276569,0.00008711451,0.0005792616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001685957,0.0003859941,0.007047596,0.0001307968,0.000222773,0.0004192063,0.002052622,0.0215617,0.01911405,0.06354764,0.7896481,0.09570099],"study_design_scores_gemma":[0.001359054,0.000007498877,0.003840768,0.00007949883,0.00005486646,0.0001315538,0.0000596982,0.06547588,0.02597108,0.05554153,0.8459315,0.001547039],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005754201,0.000005722363,0.8196456,0.007995791,0.0006950829,0.00116685,0.0002260118,0.001086402,0.1634244],"genre_scores_gemma":[0.7453404,0.0004611749,0.2001153,0.02392068,0.0008218139,0.0005732245,0.0009515943,0.0002337403,0.0275821],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7395862,"threshold_uncertainty_score":0.9998358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02543908197053936,"score_gpt":0.2649035579312501,"score_spread":0.2394644759607107,"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."}}