{"meta":{"query_hash":"23af7e3f67f4","filters":{"venue":"Informatik aktuell"},"cohort_total":4,"direct_labels_cover":0,"predictions_cover":4,"exported":4,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/23af7e3f67f4","api":"https://metacan.xera.ac/api/v1/cohort?venue=Informatik+aktuell"},"results":[{"id":"W2295279874","doi":"10.1007/978-3-642-28502-8_30","title":"Diameter Measurement of Vascular Structures in Ultrasound Video Sequences","year":2012,"lang":"en","type":"book-chapter","venue":"Informatik aktuell","topic":"Cardiovascular Health and Disease Prevention","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; University of New Brunswick","funders":"","keywords":"Ultrasound; Computer science; Acoustics; Physics","score_opus":0.02577626165599551,"score_gpt":0.25546812830742993,"score_spread":0.22969186665143443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295279874","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032504547,0.11513879,0.0014159846,0.00008670346,0.0012035667,0.004470871,0.00021430136,0.00014849479,0.84481674],"genre_scores_gemma":[0.9852692,0.005840313,0.0014884372,0.0007740781,0.00056015456,0.00006713898,0.00048230623,0.000093789466,0.0054245954],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99727124,0.000030504183,0.00092016475,0.00017705931,0.001276888,0.00032414222],"domain_scores_gemma":[0.9984755,0.000044018947,0.0003563059,0.0005917327,0.00025214453,0.00028030833],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00087899325,0.00031865275,0.0007823879,0.00035913248,0.000028959359,0.000015039718,0.000114041686,0.00033088695,0.0010932711],"category_scores_gemma":[0.00012597677,0.00027175652,0.0007567524,0.000049515824,0.00009355465,0.00023733432,0.00004136835,0.0003624809,0.0001663806],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003928178,0.00093980046,0.028991599,0.09515618,0.014991921,0.0002969121,0.010957948,0.0009416125,0.0041512805,0.076722674,0.018043052,0.7448788],"study_design_scores_gemma":[0.012385477,0.0004529491,0.17342651,0.008330983,0.00525965,0.00047885842,0.0003623593,0.000063321306,0.0027824542,0.0305084,0.7636282,0.0023208414],"about_ca_topic_score_codex":0.00014613089,"about_ca_topic_score_gemma":0.000048396352,"teacher_disagreement_score":0.95276463,"about_ca_system_score_codex":0.00026950537,"about_ca_system_score_gemma":0.0003624355,"threshold_uncertainty_score":0.9999735},"labels":[],"label_agreement":null},{"id":"W4379031899","doi":"10.1007/978-3-658-41657-7_18","title":"Deep Learning Approaches for Contrast Removal from Contrast-enhanced CT","year":2023,"lang":"en","type":"book-chapter","venue":"Informatik aktuell","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"","keywords":"Hounsfield scale; Contrast (vision); Computed tomography; Dosimetry; Nuclear medicine; Contrast enhancement; Selective internal radiation therapy; Medicine; Artificial intelligence; Computer science; Radiology; Magnetic resonance imaging","score_opus":0.02319343401328017,"score_gpt":0.24553154210956632,"score_spread":0.22233810809628615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379031899","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006114188,0.00023357084,0.60624486,0.000019257543,0.00023179207,0.0010623751,0.00036844553,0.0004922619,0.3912863],"genre_scores_gemma":[0.064104214,0.00053005444,0.122538604,0.0004925963,0.004372301,0.0011928182,0.009235629,0.0011320049,0.7964018],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99796015,0.00001541972,0.00081690337,0.0003929519,0.00029506162,0.0005194966],"domain_scores_gemma":[0.9981488,0.00039661193,0.00076459796,0.0004455944,0.000114814466,0.00012960425],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018339831,0.0006455982,0.000849298,0.00015526182,0.00021571048,0.00012650536,0.0004156996,0.00019764039,0.00087366375],"category_scores_gemma":[0.000014758075,0.0006393631,0.00043335863,0.000040392148,0.00013468573,0.00043348476,0.000080716316,0.00077332,0.00023374509],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017566359,0.000033773827,0.000053854328,0.00014115107,0.0011791437,0.000009859277,0.0012562554,0.0024377655,0.00023290237,0.32454202,0.0022749025,0.66766274],"study_design_scores_gemma":[0.0024299475,0.00021702233,0.000016685937,0.0004325544,0.00019024327,0.000006122995,0.00041562796,0.027063068,0.004094716,0.12909573,0.8343479,0.0016903556],"about_ca_topic_score_codex":0.000056390603,"about_ca_topic_score_gemma":0.000008433805,"teacher_disagreement_score":0.83207303,"about_ca_system_score_codex":0.00009616614,"about_ca_system_score_gemma":0.000069831665,"threshold_uncertainty_score":0.9996058},"labels":[],"label_agreement":null},{"id":"W4391934971","doi":"10.1007/978-3-658-44037-4_5","title":"Abstract: Cytologic Scoring of Equine Exercise-induced Pulmonary Hemorrhage","year":2024,"lang":"en","type":"book-chapter","venue":"Informatik aktuell","topic":"Veterinary Orthopedics and Neurology","field":"Veterinary","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Medicine; Pulmonary hemorrhage; Cardiology; Internal medicine; Lung","score_opus":0.07464850865772517,"score_gpt":0.2987758731041223,"score_spread":0.22412736444639714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391934971","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10051603,0.0018009817,0.000006489363,0.000085598345,0.0015716959,0.00058329414,0.00025831768,0.0003076046,0.89487],"genre_scores_gemma":[0.90519404,0.0007588973,0.0001352795,0.00021914879,0.00032623496,0.00003426439,0.0002030011,0.00017493416,0.09295422],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968451,0.00000954448,0.001531813,0.0005235367,0.0005147917,0.0005751931],"domain_scores_gemma":[0.99808586,0.00011083414,0.0005239197,0.00097612164,0.00011626341,0.00018698032],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003184305,0.00077994715,0.0010902927,0.00058414927,0.00009363116,0.000059179016,0.00065995124,0.0008528709,0.0036388822],"category_scores_gemma":[0.000016863363,0.0007280614,0.0004977637,0.00007936628,0.00015823939,0.00042476057,0.00084271084,0.0013032027,0.0058693984],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011544243,0.0009977858,0.00023846672,0.06680239,0.0020122707,0.2367533,0.0050156047,0.0002050207,0.14478259,0.15268645,0.016477011,0.36248487],"study_design_scores_gemma":[0.0029542241,0.025398992,0.0010415831,0.0101026865,0.0018675383,0.049132805,0.00032621465,0.0063020713,0.003510708,0.06000874,0.8311982,0.00815622],"about_ca_topic_score_codex":0.000025985872,"about_ca_topic_score_gemma":0.0000024873373,"teacher_disagreement_score":0.8147212,"about_ca_system_score_codex":0.00006309125,"about_ca_system_score_gemma":0.00009393056,"threshold_uncertainty_score":0.999517},"labels":[],"label_agreement":null},{"id":"W4408075062","doi":"10.1007/978-3-658-47422-5_60","title":"Abstract: Würstchen","year":2025,"lang":"de","type":"book-chapter","venue":"Informatik aktuell","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Medicine","score_opus":0.015462444479195897,"score_gpt":0.21917700775872492,"score_spread":0.20371456327952903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408075062","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000049629566,0.0018203852,0.15301012,0.0008231453,0.0037994557,0.00059098226,0.00011846945,0.00017515029,0.83965737],"genre_scores_gemma":[0.07479912,0.0075401333,0.062192366,0.011379545,0.0047251186,0.00007662661,0.00053459586,0.00019339878,0.8385591],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960295,0.000033349545,0.0015703145,0.00070436875,0.00081765326,0.00084483915],"domain_scores_gemma":[0.9962154,0.00036846587,0.00091248815,0.0016863197,0.0004911695,0.00032612905],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000609977,0.0010007224,0.00097201177,0.00045100783,0.00048629084,0.0009937894,0.002242719,0.0007587483,0.0042121317],"category_scores_gemma":[0.000097991644,0.00096401136,0.00060571654,0.00019209457,0.00025950317,0.0018167506,0.0011602413,0.0010743778,0.019678129],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004533983,0.00006886489,0.000015302177,0.0006137793,0.0007410617,0.00009319269,0.0019346728,0.0035698263,0.000043998105,0.30190644,0.17417826,0.51678926],"study_design_scores_gemma":[0.00044969216,0.0000748462,0.00011027498,0.00078965566,0.000129256,0.000008647616,0.000037212234,0.043224365,0.00043718296,0.0058816453,0.9477936,0.0010636296],"about_ca_topic_score_codex":0.00010949334,"about_ca_topic_score_gemma":0.000021187883,"teacher_disagreement_score":0.77361536,"about_ca_system_score_codex":0.00016737342,"about_ca_system_score_gemma":0.000484824,"threshold_uncertainty_score":0.99928105},"labels":[],"label_agreement":null}]}