{"id":"W7108475199","doi":"10.3886/e240894","title":"HIFLD OPEN North American Rail Network Nodes","year":2025,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rail network; Rail transportation; Flow network; Network topology; Transportation infrastructure; State (computer science); Rail transit","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001350047,0.001904794,0.001259659,0.00400423,0.001490539,0.002836037,0.003649002,0.001862238,0.06111841],"category_scores_gemma":[0.007434608,0.0006578267,0.00141967,0.007033312,0.0004662057,0.003188943,0.002752012,0.002213421,0.08439233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001852828,"about_ca_system_score_gemma":0.003321498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05815426,"about_ca_topic_score_gemma":0.09058349,"domain_scores_codex":[0.9983764,0.0002787647,0.000164657,0.0004615837,0.0004602904,0.0002584528],"domain_scores_gemma":[0.9975463,0.0004572099,0.0001654263,0.0007006305,0.0008580154,0.0002724915],"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":[0.00002183212,0.00001252921,0.000388926,0.0001423057,0.000008383249,0.00001321396,0.00002075781,0.0003718731,0.00003392365,0.0007620376,0.9957451,0.002479187],"study_design_scores_gemma":[0.0000674523,0.000009382826,0.001436378,0.0001751632,0.00000892293,0.00003653394,0.000107741,0.001513215,0.0001560068,0.002239577,0.9942262,0.00002354403],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002554428,0.00008929456,0.0002796253,0.0001962555,0.00008306713,0.00002188316,0.9953904,0.001385676,0.002298279],"genre_scores_gemma":[0.0004520331,0.00005700279,0.0004834741,0.00005828076,0.0000116882,0.00006647968,0.9978632,0.0001249897,0.0008828987],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06111841,"threshold_uncertainty_score":0.2044615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06548407649554025,"score_gpt":0.3546159612433364,"score_spread":0.2891318847477962,"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."}}