{"meta":{"query_hash":"35804fcff231","filters":{"venue":"International Integrated Intelligent Systems"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"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/35804fcff231","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Integrated+Intelligent+Systems"},"results":[{"id":"W4399287558","doi":"10.21608/iiis.2024.357817","title":"Brain Tumor Detection Using GLCM and Machine learning Techniques","year":2024,"lang":"en","type":"article","venue":"International Integrated Intelligent Systems","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Artificial intelligence; Computer science","score_opus":0.06292619900746944,"score_gpt":0.3110993944742732,"score_spread":0.24817319546680378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399287558","genre_codex":"methods","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":[0.45442915,0.0016606833,0.5125236,0.0022065223,0.012528717,0.0012802421,0.000111017995,0.0033471219,0.011912928],"genre_scores_gemma":[0.9950698,0.00009937186,0.00010585467,0.00025638237,0.000278643,0.000065105996,0.0000142116405,0.000043009153,0.004067598],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981689,0.0002492905,0.00046756875,0.00055284746,0.00036687937,0.0001945095],"domain_scores_gemma":[0.99921167,0.00030817202,0.00013059986,0.00013473375,0.00013179194,0.000083026134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043726774,0.00021730068,0.00015867509,0.00051184656,0.00017019897,0.00064028683,0.00022088007,0.000091213115,0.00016586744],"category_scores_gemma":[0.0007659823,0.00018739111,0.00007896011,0.00046613347,0.00009938825,0.0003488316,0.000049335806,0.00052542094,0.00014163427],"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":[0.000039081082,0.000030455876,0.0000819279,0.000047872487,0.000027254222,0.000044299493,0.00018469701,0.00021012708,0.96272403,0.008807045,0.00014194284,0.027661292],"study_design_scores_gemma":[0.00003329094,0.000049036524,0.000009456948,0.00017563347,0.0000061762057,0.0006129366,0.00023512274,0.3725343,0.48414704,0.00013142041,0.14194119,0.00012440242],"about_ca_topic_score_codex":0.0005820231,"about_ca_topic_score_gemma":0.000028601873,"teacher_disagreement_score":0.54064065,"about_ca_system_score_codex":0.00037393338,"about_ca_system_score_gemma":0.00004313604,"threshold_uncertainty_score":0.7641588},"labels":[],"label_agreement":null}]}