{"id":"W6968268434","doi":"10.5281/zenodo.14222248","title":"EU_mgmtEAS","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Environmental and Biological Research in Conflict Zones","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Code (set theory); Identification (biology); Natural (archaeology); Table (database)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004121181,0.001882301,0.001961506,0.007702854,0.001298191,0.007010475,0.004167235,0.005296438,0.4179389],"category_scores_gemma":[0.01714893,0.001151793,0.001569784,0.01183371,0.001056483,0.003902379,0.004793997,0.003025438,0.3619848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003252351,"about_ca_system_score_gemma":0.00758101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02262923,"about_ca_topic_score_gemma":0.009984517,"domain_scores_codex":[0.9944564,0.0007943606,0.0005636827,0.0006042866,0.002867737,0.0007134932],"domain_scores_gemma":[0.9930321,0.001423987,0.0007552705,0.001763217,0.002442044,0.0005833543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001567492,0.00004286829,0.0002191001,0.0004672112,0.00002341,0.00003526008,0.00004948384,0.0003036466,0.0003504109,0.01607574,0.9495885,0.03268752],"study_design_scores_gemma":[0.00004009787,0.00001237845,0.0005689347,0.0001298315,0.000007458267,0.00001784088,0.00001662132,0.0001060243,0.0003050437,0.003516273,0.9952631,0.00001640557],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0005069849,0.001040136,0.003885031,0.00389235,0.002866688,0.0002321234,0.7496462,0.00952591,0.2284045],"genre_scores_gemma":[0.006321323,0.001595069,0.008864609,0.004489007,0.0005089329,0.001195637,0.7545125,0.007288275,0.2152247],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5820611,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02981447455198259,"score_gpt":0.2524434101564968,"score_spread":0.2226289356045142,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}