{"id":"W4403208981","doi":"10.2139/ssrn.4980474","title":"Using Triple Point Alone to Predict Saturation Line","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Triple point; Saturation (graph theory); Point (geometry); Mathematics; Statistics; Computer science; Geometry; Physics; Combinatorics; Thermodynamics","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":[0.0002306963,0.000603414,0.000517885,0.001606923,0.0003810752,0.0009101338,0.0004592492,0.0009430987,0.005423686],"category_scores_gemma":[0.00126392,0.0002308269,0.0003553925,0.0009748353,0.0002069062,0.0009877327,0.0004062103,0.0008196204,0.003411073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003772303,"about_ca_system_score_gemma":0.0002299351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002390111,"about_ca_topic_score_gemma":0.002692271,"domain_scores_codex":[0.9998907,0.00001133664,0.000004322207,0.0000307932,0.00004004674,0.00002280404],"domain_scores_gemma":[0.9993203,0.0001998645,0.0000751569,0.00007155801,0.0002580993,0.00007502585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003345014,0.0005727847,0.1342576,0.0005476392,0.000219833,0.00123483,0.0002954134,0.2641978,0.2480366,0.003010617,0.01332999,0.330952],"study_design_scores_gemma":[0.00002477096,0.0003248076,0.01854208,0.00003111037,0.00004705448,0.0002456237,0.00008994412,0.925421,0.0504658,0.002780285,0.001988455,0.00003910154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.768223,0.0008042469,0.201263,0.0001754341,0.0002959514,0.00009385179,0.002258375,0.005833576,0.02105241],"genre_scores_gemma":[0.9922783,0.00008142051,0.005405047,0.00001737036,0.00001409695,0.00001221832,0.0003528884,0.00009149406,0.001747142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005423686,"threshold_uncertainty_score":0.01814407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02289327137995766,"score_gpt":0.2890869613519072,"score_spread":0.2661936899719495,"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."}}