{"meta":{"query_hash":"57a2cdf482e7","filters":{"venue":"Digital Dentistry Journal"},"cohort_total":5,"direct_labels_cover":0,"predictions_cover":5,"exported":5,"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/57a2cdf482e7","api":"https://metacan.xera.ac/api/v1/cohort?venue=Digital+Dentistry+Journal"},"results":[{"id":"W4409902355","doi":"10.1016/j.ddj.2025.100013","title":"Optimizing CBCT analysis of the Adenoid region: A deep learning approach","year":2025,"lang":"en","type":"article","venue":"Digital Dentistry Journal","topic":"Obstructive Sleep Apnea Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Faculty of Medicine and Dentistry, University of Alberta; University of Alberta; American Academy of Oral and Maxillofacial Radiology","keywords":"Adenoid; Deep learning; Artificial intelligence; Computer science; Medicine; Surgery","score_opus":0.02019699168710607,"score_gpt":0.2960148026655236,"score_spread":0.2758178109784175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409902355","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04456182,0.000585594,0.9512562,0.00023330381,0.000028389712,0.000106449705,0.00020733004,0.0016433275,0.001377593],"genre_scores_gemma":[0.48681313,0.00041861393,0.50689775,0.00034898636,0.000040211835,0.00018820344,0.00090081245,0.00021472231,0.0041775955],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969816,0.000042875683,0.000024611947,0.00010209349,0.000084505315,0.000047709957],"domain_scores_gemma":[0.99968004,0.000114448165,0.000034683824,0.000033492008,0.0001200062,0.000017368784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007590312,0.0008261211,0.0005962714,0.001016092,0.00026348038,0.0007823145,0.00093659904,0.00093591627,0.0016470483],"category_scores_gemma":[0.0015132567,0.0004227107,0.0006653145,0.00069135835,0.00031950136,0.00053897314,0.00070187636,0.0007477529,0.00064540777],"study_design_candidate":"simulation_or_modeling","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":[0.00021080568,0.00015858363,0.005144781,0.0001654388,0.00009963967,0.00019042089,0.00007572664,0.3940108,0.037999377,0.0022252218,0.003011615,0.55670756],"study_design_scores_gemma":[0.000004751491,0.000025379679,0.0006163481,0.000009252499,0.000011680982,0.00004661169,0.000010073391,0.9932493,0.0047374824,0.00075655605,0.0005268314,0.0000057135026],"about_ca_topic_score_codex":0.012980176,"about_ca_topic_score_gemma":0.014493286,"teacher_disagreement_score":0.012980176,"about_ca_system_score_codex":0.0010972228,"about_ca_system_score_gemma":0.0014373556,"threshold_uncertainty_score":0.025809228},"labels":[],"label_agreement":null},{"id":"W4412055395","doi":"10.1016/j.ddj.2025.100024","title":"Trueness and precision of different intraoral scanners for shade assessment under variable light conditions-a cross-sectional study","year":2025,"lang":"en","type":"article","venue":"Digital Dentistry Journal","topic":"Dental materials and restorations","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Dentistry; Statistics; Mathematics; Orthodontics; Medicine","score_opus":0.019369258494053708,"score_gpt":0.3567445435774021,"score_spread":0.3373752850833484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412055395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98890126,0.0026555683,0.007303893,0.000015038864,0.000036100555,0.00007703633,0.00012695281,0.000050137343,0.0008340142],"genre_scores_gemma":[0.9936487,0.00046089565,0.005278604,0.000025361836,0.000034541074,0.000043684126,0.0001068312,0.00003459712,0.00036674368],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9944705,0.0014687363,0.000494573,0.0014374453,0.0019678732,0.0001608482],"domain_scores_gemma":[0.9800802,0.008085217,0.0038133631,0.002608549,0.00506888,0.00034389415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008847694,0.00068084954,0.0006214713,0.0017940574,0.00043347426,0.00091067504,0.0004942161,0.0008454838,0.0013956159],"category_scores_gemma":[0.012306459,0.00089246844,0.0007137501,0.000745313,0.0008966471,0.00084501837,0.0006594735,0.0003751892,0.0005158768],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025590006,0.00048061385,0.8730334,0.00058241165,0.00073369156,0.00041860458,0.0024147637,0.0006145922,0.058997933,0.00015521745,0.00027916342,0.059730675],"study_design_scores_gemma":[0.000035691137,0.0023297274,0.9790492,0.000065900706,0.00041355306,0.0019903814,0.000715458,0.0014158285,0.012581961,0.00013134925,0.001214104,0.000056813868],"about_ca_topic_score_codex":0.0008343609,"about_ca_topic_score_gemma":0.0013833487,"teacher_disagreement_score":0.008847694,"about_ca_system_score_codex":0.00023167007,"about_ca_system_score_gemma":0.00028770068,"threshold_uncertainty_score":0.046791673},"labels":[],"label_agreement":null},{"id":"W4414826916","doi":"10.1016/j.ddj.2025.100040","title":"REMOVED: Human-AI collaboration for mandibular canal tracing accuracy on cone-beam computed tomography: A multi-evaluator study","year":2025,"lang":"en","type":"article","venue":"Digital Dentistry Journal","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Spinal Cord Injury Alberta; University of Alberta","funders":"Faculty of Medicine and Dentistry, University of Alberta; University of Alberta","keywords":"Tracing; Reliability (semiconductor); Hausdorff distance; Reproducibility; Boundary (topology); Similarity (geometry); Ground truth","score_opus":0.023330231911157583,"score_gpt":0.3490855081094785,"score_spread":0.32575527619832095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414826916","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9837427,0.00083565095,0.011954582,0.00011620783,0.00007456412,0.00033676767,0.0001843056,0.00014734187,0.0026078853],"genre_scores_gemma":[0.99345785,0.000103514096,0.005120492,0.00006990607,0.000034242403,0.00024558738,0.000114128714,0.00010295214,0.0007514694],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9698683,0.01903524,0.0021315112,0.0033606663,0.004772643,0.000831663],"domain_scores_gemma":[0.8056334,0.112889916,0.01302611,0.014365281,0.050284673,0.003800557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.047176182,0.00075672957,0.0007473984,0.0015839881,0.0011107742,0.0021267121,0.00095500605,0.0009651975,0.0029777791],"category_scores_gemma":[0.10678602,0.000428306,0.0010617762,0.00069578824,0.0012199566,0.0018311283,0.0025654119,0.0005166506,0.0011271649],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010203792,0.0016302246,0.68576735,0.0013918774,0.0013722769,0.0007288219,0.04159024,0.0031328546,0.018145412,0.0005566941,0.0028976437,0.23258285],"study_design_scores_gemma":[0.0004167348,0.012917239,0.91418755,0.000621865,0.001181376,0.0026193182,0.014417692,0.022007579,0.017233344,0.0012500413,0.01277363,0.0003736385],"about_ca_topic_score_codex":0.0011889652,"about_ca_topic_score_gemma":0.0020897444,"teacher_disagreement_score":0.047176182,"about_ca_system_score_codex":0.0010096562,"about_ca_system_score_gemma":0.0012847803,"threshold_uncertainty_score":0.2494945},"labels":[],"label_agreement":null},{"id":"W4415269518","doi":"10.1016/j.ddj.2025.100042","title":"AI-driven analysis of jaw-bone alterations in CBCT images associated with systemic diseases: A systematic review","year":2025,"lang":"en","type":"article","venue":"Digital Dentistry Journal","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Cone beam computed tomography; Temporomandibular joint; Convolutional neural network; Osteoporosis; Osteoarthritis; Computed tomography; Medical imaging; Artificial neural network","score_opus":0.0066951865907530096,"score_gpt":0.2725054828860897,"score_spread":0.2658102962953367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415269518","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008678891,0.9976344,0.000333564,0.00018160793,0.00008046601,0.00020455099,0.0004906504,0.000010246889,0.00019660746],"genre_scores_gemma":[0.019247333,0.9765663,0.0017927702,0.00076936994,0.00016501924,0.0006941769,0.0006157061,0.000014867619,0.00013438365],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9914829,0.0027067438,0.0034132053,0.0008059852,0.0014365588,0.0001546467],"domain_scores_gemma":[0.94508654,0.04491101,0.0056882976,0.0008483944,0.0032653417,0.00020048619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008635222,0.0016612096,0.007732394,0.009629936,0.0005103892,0.0031338139,0.0023205248,0.0019954778,0.0042128065],"category_scores_gemma":[0.0659497,0.0009765988,0.009154627,0.0072050653,0.00074884575,0.0022463151,0.0012451848,0.0009774193,0.00041163067],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016070719,0.000016452286,0.0011692047,0.9382841,0.011353356,0.00006263887,0.000108026616,0.00017043827,0.00013867136,0.0002141948,0.0013241025,0.046998065],"study_design_scores_gemma":[0.0002256739,0.00019287306,0.006843715,0.8727872,0.09851933,0.00047767005,0.00020717396,0.0003086044,0.00024980344,0.0005671515,0.019555895,0.00006487567],"about_ca_topic_score_codex":0.0077330796,"about_ca_topic_score_gemma":0.02043513,"teacher_disagreement_score":0.009629936,"about_ca_system_score_codex":0.0025735414,"about_ca_system_score_gemma":0.008117822,"threshold_uncertainty_score":0.045667946},"labels":[],"label_agreement":null},{"id":"W4416724082","doi":"10.1016/j.ddj.2025.100049","title":"A novel digital technique for screw-access retrieval system fabrication: A technique paper","year":2025,"lang":"en","type":"article","venue":"Digital Dentistry Journal","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Identification (biology); Implant; Image retrieval; Data retrieval; Key (lock)","score_opus":0.016357342147858833,"score_gpt":0.2976539323588166,"score_spread":0.28129659021095776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416724082","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14799021,0.0059737447,0.8185315,0.0011532705,0.0012134298,0.00071016257,0.00029932096,0.002522056,0.021606335],"genre_scores_gemma":[0.26919898,0.002125129,0.7158816,0.00037484866,0.0002466838,0.00013517594,0.00016046663,0.00015471934,0.011722498],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994641,0.000031690626,0.000057790607,0.00010701903,0.00030656188,0.00003285607],"domain_scores_gemma":[0.99958664,0.00010360406,0.00007951823,0.00012563488,0.00007249669,0.00003219639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047453956,0.00043907738,0.00021370103,0.0010427574,0.00039903502,0.00085569307,0.0007243137,0.00062609004,0.0043531656],"category_scores_gemma":[0.00079587474,0.00037220365,0.0004397266,0.00050662435,0.000657356,0.0011626136,0.0008219903,0.0008205352,0.0012619524],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014286836,0.00014125332,0.0018000596,0.0006014931,0.00003604006,0.0016029233,0.00031025553,0.00059680856,0.6663789,0.005568401,0.004643506,0.3181775],"study_design_scores_gemma":[0.00018240171,0.0015997001,0.01037067,0.0001332493,0.00017896929,0.06597889,0.00025057883,0.012007773,0.66311556,0.0020870708,0.24386317,0.00023199475],"about_ca_topic_score_codex":0.00032087715,"about_ca_topic_score_gemma":0.00078131654,"teacher_disagreement_score":0.0043531656,"about_ca_system_score_codex":0.00028376188,"about_ca_system_score_gemma":0.000679104,"threshold_uncertainty_score":0.014562786},"labels":[],"label_agreement":null}]}