{"meta":{"query_hash":"978d0c196bd8","filters":{"venue":"Archiwum Odlewnictwa"},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"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/978d0c196bd8","api":"https://metacan.xera.ac/api/v1/cohort?venue=Archiwum+Odlewnictwa"},"results":[{"id":"W1833252647","doi":"","title":"ZASTOSOWANIE SIECI NEURONOWYCH DO MODELOWANIA TEMPERATURY SOLIDUS PODEUTEKTYCZNYCH STOPÓW Al-Si-Cu","year":2006,"lang":"pl","type":"article","venue":"Archiwum Odlewnictwa","topic":"Induction Heating and Inverter Technology","field":"Engineering","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 Windsor","funders":"","keywords":"Solidus; Physics; Materials science; Metallurgy","score_opus":0.008374784338822713,"score_gpt":0.20558949088660203,"score_spread":0.1972147065477793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1833252647","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":[0.72965777,0.0011007006,0.2500338,0.00027455724,0.00014248966,0.000089187306,0.0008358473,0.0012247192,0.016641088],"genre_scores_gemma":[0.9810945,0.0006066149,0.012403087,0.000022491024,0.0000058001847,0.000057721667,0.00027693983,0.00009015665,0.0054427194],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999132,0.0000073080687,0.0000047744097,0.000028597788,0.000035684938,0.000010432765],"domain_scores_gemma":[0.9999387,0.000019928157,0.0000072261982,0.0000139560925,0.000016776694,0.0000033374415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011959117,0.00029520327,0.00037955635,0.0001604032,0.00019111906,0.00061478565,0.00045599218,0.00032579128,0.0026145445],"category_scores_gemma":[0.00030019134,0.00016665866,0.00036952112,0.00029194064,0.00031663757,0.000573694,0.00029049077,0.00035450983,0.0004051798],"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":[0.0008054933,0.000113039736,0.0042960853,0.0006820983,0.00010676321,0.00032227783,0.00039821496,0.23080312,0.6952127,0.01163673,0.0011867331,0.054436777],"study_design_scores_gemma":[0.000044578443,0.00048660554,0.003992936,0.000026876818,0.00011375929,0.00024775145,0.00021391214,0.59090203,0.38714427,0.006071439,0.010701699,0.00005414669],"about_ca_topic_score_codex":0.0027470826,"about_ca_topic_score_gemma":0.0024828564,"teacher_disagreement_score":0.0027470826,"about_ca_system_score_codex":0.0004956427,"about_ca_system_score_gemma":0.00046928128,"threshold_uncertainty_score":0.008746564},"labels":[],"label_agreement":null},{"id":"W899774621","doi":"","title":"ZASTOSOWANIE METOD SZTUCZNEJ INTELIGENCJI DO KLASYFIKACJI WAD W ODLEWACH ZE STOPÓW Al-Si-Cu","year":2006,"lang":"pl","type":"article","venue":"Archiwum Odlewnictwa","topic":"Surface Treatment and Coatings","field":"Engineering","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 Windsor","funders":"","keywords":"Physics; Theology; Philosophy","score_opus":0.009005711310030409,"score_gpt":0.21558013929740344,"score_spread":0.20657442798737302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W899774621","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":[0.8519037,0.0086753275,0.058265474,0.0008387683,0.00047053717,0.00026438816,0.00048623927,0.0008510127,0.07824451],"genre_scores_gemma":[0.943568,0.0028837083,0.022180613,0.0001384613,0.000052165444,0.000114979855,0.00029959765,0.00014908786,0.030613303],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993131,0.000050476217,0.0000389166,0.00011552315,0.00039504166,0.000086956956],"domain_scores_gemma":[0.99962056,0.00007802741,0.000050771374,0.00007158764,0.00014668364,0.000032401214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004465392,0.0004503338,0.00049220043,0.0007610364,0.00052178645,0.0020452773,0.00053886784,0.0006320649,0.006475649],"category_scores_gemma":[0.00077045173,0.00030526685,0.00033024527,0.00058371003,0.0005830461,0.00090614083,0.00069301605,0.0005832212,0.0013815818],"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":[0.00055973354,0.00015339171,0.004916145,0.0010761668,0.000063463354,0.00039887725,0.00079092494,0.0029900793,0.85856277,0.0059370166,0.0017890149,0.12276239],"study_design_scores_gemma":[0.000049626186,0.0014025022,0.023058878,0.000093233866,0.0001875323,0.0012072367,0.0019408297,0.009781444,0.87120944,0.0041494453,0.08682081,0.00009906555],"about_ca_topic_score_codex":0.0013238406,"about_ca_topic_score_gemma":0.0028154415,"teacher_disagreement_score":0.006475649,"about_ca_system_score_codex":0.00055880763,"about_ca_system_score_gemma":0.0007558153,"threshold_uncertainty_score":0.021663249},"labels":[],"label_agreement":null}]}