{"meta":{"query_hash":"bdc9137ded8f","filters":{"venue":"LCGC Europe"},"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/bdc9137ded8f","api":"https://metacan.xera.ac/api/v1/cohort?venue=LCGC+Europe"},"results":[{"id":"W4312871235","doi":"10.56530/lcgc.eu.gi5670v6","title":"Multivariate Optimization Procedure for Dynamic Headspace Extractions Coupled to GC(×GC)","year":2022,"lang":"en","type":"article","venue":"LCGC Europe","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":3,"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":"Extraction (chemistry); Reproducibility; Multivariate statistics; Water content; Moisture; Sample (material); Sample preparation; Gas chromatography; Chromatography; Process engineering; Computer science; Environmental science; Chemistry; Engineering; Machine learning; Organic chemistry","score_opus":0.0408127661287583,"score_gpt":0.3137113509735177,"score_spread":0.27289858484475943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312871235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5300071,0.00012753071,0.43799117,0.02609881,0.0007482683,0.001909202,0.00084087404,0.00033608422,0.0019409277],"genre_scores_gemma":[0.90040725,0.000016482692,0.08789519,0.0021928994,0.00018660272,0.00025935582,0.000353375,0.000005694842,0.008683142],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998964,0.00019741338,0.00017351101,0.00030991918,0.00015252033,0.00020262529],"domain_scores_gemma":[0.9992709,0.00042293797,0.0000485238,0.000054680742,0.000102431666,0.00010052021],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00029305954,0.00010054321,0.00014627354,0.000015049536,0.0005914556,0.000049919166,0.0001501733,0.000023520122,0.001202287],"category_scores_gemma":[0.00053844263,0.000044985976,0.00006869695,0.0005993403,0.000014021693,0.000047608613,0.000061799255,0.000108700864,0.00001579614],"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":[0.00034215275,0.00052366604,0.00033071177,0.000018090774,0.00006345826,0.00001352576,0.00023746524,0.4291229,0.5257391,0.0052880347,0.0029764941,0.035344433],"study_design_scores_gemma":[0.00026097565,0.0007509722,0.028887225,0.0000068787745,0.00007081471,0.000011502278,0.00041362314,0.8544507,0.00026089634,0.0003914104,0.1141494,0.0003456262],"about_ca_topic_score_codex":0.000057169633,"about_ca_topic_score_gemma":0.000075120784,"teacher_disagreement_score":0.5254782,"about_ca_system_score_codex":0.000027461578,"about_ca_system_score_gemma":0.000006901189,"threshold_uncertainty_score":0.99971074},"labels":[],"label_agreement":null}]}