{"id":"W6977445149","doi":"10.6084/m9.figshare.21375534.v3","title":"BIOL3250 -- BIOBLITZ (DATA & METADATA FOR FIELD EXPERIMENT).xlsx","year":2022,"lang":"en","type":"dataset","venue":"INDIGO (University of Illinois at Chicago)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metadata; Species richness; Field (mathematics); Tracking (education); Diversity (politics); Biodiversity","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002033867,0.002194017,0.001919577,0.003186672,0.001112321,0.002592095,0.003226901,0.002105382,0.4194265],"category_scores_gemma":[0.008657321,0.001067292,0.001306548,0.005446887,0.0005112206,0.00218647,0.002363451,0.001714761,0.305345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001175407,"about_ca_system_score_gemma":0.002081194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02159255,"about_ca_topic_score_gemma":0.04305551,"domain_scores_codex":[0.9988956,0.0002046327,0.0001320938,0.0003527667,0.0002296006,0.0001852338],"domain_scores_gemma":[0.9945894,0.002168994,0.0004538282,0.001200121,0.00112633,0.0004611807],"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":[0.00005880832,0.00002251999,0.0007103606,0.0006175371,0.00002155714,0.000008583445,0.00002683886,0.0001741589,0.0001010002,0.0002562305,0.9964007,0.001601745],"study_design_scores_gemma":[0.0006389036,0.00003429503,0.005127215,0.0003514344,0.00004513537,0.00002227659,0.0001044833,0.0003663106,0.0004202917,0.001637003,0.9912021,0.00005059277],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005018385,0.000009696517,0.00007124033,0.00002589998,0.00001421992,0.00001001197,0.9988956,0.0004252194,0.0004978822],"genre_scores_gemma":[0.0004028159,0.00002298487,0.0007038304,0.00007007565,0.000009472156,0.0002626638,0.9965347,0.0005205144,0.001472851],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4194265,"threshold_uncertainty_score":0.8281176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06946127424782897,"score_gpt":0.2891474186417046,"score_spread":0.2196861443938756,"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."}}