{"id":"W2148023989","doi":"","title":"COMPUTATIONAL PLACENTAL PATHOLOGY: USING PLACENTAL GEOMETRY TO ASSESS PLACENTAL FUNCTION","year":2009,"lang":"en","type":"dissertation","venue":"Summit (Simon Fraser University)","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Mitacs","keywords":"Placenta; Obstetrics; Fetus; Chorionic villi; Placenta Diseases; Medicine; Andrology; Biology; Pregnancy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0003886235,0.0007489752,0.0004703857,0.001751492,0.0002076472,0.001451575,0.0007945275,0.0005933701,0.001773275],"category_scores_gemma":[0.002896591,0.0005061429,0.0005970593,0.0009273951,0.0005724317,0.0006395123,0.0007997109,0.0003940009,0.0004662715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000533296,"about_ca_system_score_gemma":0.0006111361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003507221,"about_ca_topic_score_gemma":0.002851463,"domain_scores_codex":[0.9998137,0.00005082638,0.000008588109,0.00004010079,0.00007099009,0.00001568835],"domain_scores_gemma":[0.9994399,0.0002854055,0.00008489912,0.00007715709,0.00008124364,0.00003137327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001737487,0.00005988988,0.009676343,0.0002083526,0.0001297569,0.0005062943,0.0002869187,0.6462784,0.02488809,0.01126004,0.003414653,0.3031176],"study_design_scores_gemma":[0.00001339862,0.00004383448,0.002984117,0.00002014068,0.00002722441,0.0003344037,0.00007097697,0.9813804,0.005690531,0.007355545,0.00206086,0.00001843421],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0980867,0.00169321,0.8924015,0.0006336175,0.00009095633,0.0001317381,0.0004810337,0.001857852,0.004623401],"genre_scores_gemma":[0.6433708,0.00238481,0.3498841,0.0001029794,0.00009357151,0.0001097433,0.0006776823,0.0004110688,0.002965282],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003507221,"threshold_uncertainty_score":0.006973624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02081103436356281,"score_gpt":0.2657646438672258,"score_spread":0.244953609503663,"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."}}