{"id":"W4416992898","doi":"10.69631/g47x8w91","title":"MAGNET: Medial Axis Guided Network Extraction Tool","year":2025,"lang":"en","type":"article","venue":"InterPore journal.","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Skeletonization; Medial axis; Point (geometry); Segmentation; Image processing; Watershed; Distance transform; Quadrilateral; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006080582,0.001381484,0.0007838144,0.002298676,0.0005355576,0.001622887,0.00176817,0.001312266,0.01745148],"category_scores_gemma":[0.002185716,0.0008139656,0.001581682,0.001057421,0.0004944906,0.001712647,0.001286139,0.001212645,0.00488589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006092141,"about_ca_system_score_gemma":0.001249254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002195255,"about_ca_topic_score_gemma":0.004288298,"domain_scores_codex":[0.9995458,0.00005057987,0.00003490878,0.00009167982,0.0002338241,0.00004330751],"domain_scores_gemma":[0.9994313,0.0002776915,0.00007670779,0.0000508241,0.0001311362,0.00003223987],"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":[0.0005912468,0.0001526896,0.003275251,0.001280223,0.0002379241,0.001208851,0.0006118295,0.1607332,0.06731634,0.05857928,0.08900745,0.6170056],"study_design_scores_gemma":[0.00007909921,0.00005435331,0.0005343091,0.00007147436,0.00002976345,0.0004460269,0.00005841835,0.8942378,0.03252927,0.01677683,0.05512268,0.00006001085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003553019,0.0001455884,0.9572939,0.0001016033,0.00004142681,0.00009326011,0.001444093,0.03531012,0.00201707],"genre_scores_gemma":[0.04594329,0.0001993229,0.9430745,0.0001160239,0.00003094946,0.0004042066,0.00329762,0.003340053,0.003594053],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01745148,"threshold_uncertainty_score":0.05838096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006517336222259456,"score_gpt":0.2656698360410296,"score_spread":0.2591524998187701,"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."}}