{"id":"W1993358196","doi":"10.1109/memea.2013.6549766","title":"A crowdsourcing web platform - hip joint segmentation by non-expert contributors","year":2013,"lang":"en","type":"article","venue":"","topic":"Hip disorders and treatments","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Crowdsourcing; Segmentation; Computer science; Process (computing); Joint (building); Image segmentation; Web application; Scale-space segmentation; Artificial intelligence; Machine learning; Information retrieval; Human–computer interaction; Computer vision; World Wide Web; Engineering","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":[0.003077426,0.001190456,0.00125469,0.003144942,0.001364683,0.001735748,0.00206089,0.001873522,0.008873619],"category_scores_gemma":[0.005435407,0.0004455035,0.0008230559,0.00169709,0.0006562937,0.001313455,0.003820858,0.000770773,0.007551803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006155754,"about_ca_system_score_gemma":0.001377706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003104764,"about_ca_topic_score_gemma":0.0035303,"domain_scores_codex":[0.9965798,0.0009976508,0.000135818,0.0007543152,0.001320311,0.0002120684],"domain_scores_gemma":[0.9950874,0.00191235,0.0003051822,0.00111362,0.001004044,0.000577371],"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":[0.003258959,0.001101447,0.009142811,0.001285596,0.0003905409,0.002939752,0.003129108,0.02874993,0.1119832,0.008244566,0.04479346,0.7849807],"study_design_scores_gemma":[0.0005802914,0.001174311,0.02877492,0.0004801074,0.0002800567,0.002152168,0.002707863,0.5337387,0.121113,0.04954135,0.2588068,0.0006505107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05589437,0.000592049,0.8909312,0.0006441312,0.0003511915,0.002305153,0.003483226,0.02607443,0.01972431],"genre_scores_gemma":[0.3822477,0.0004429488,0.5690476,0.0005736673,0.0003651424,0.002730183,0.008156393,0.00193279,0.03450349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008873619,"threshold_uncertainty_score":0.0296852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01436864202034327,"score_gpt":0.2621189847158638,"score_spread":0.2477503426955205,"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."}}