{"id":"W6887261224","doi":"10.15468/dl.vgetm9","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Cyberloafing and Workplace Behavior","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Range (aeronautics); State (computer science); Identification (biology)","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":[0.0009230957,0.002091599,0.001513403,0.004661718,0.0009735308,0.002308842,0.002823395,0.002125952,0.1156708],"category_scores_gemma":[0.005067453,0.0008212078,0.00117389,0.008656854,0.0004752761,0.001967654,0.002324034,0.002009737,0.1765067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001484595,"about_ca_system_score_gemma":0.002164683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01955822,"about_ca_topic_score_gemma":0.03596119,"domain_scores_codex":[0.9990281,0.0001420111,0.0001219395,0.0003501923,0.0002048983,0.0001529622],"domain_scores_gemma":[0.9979495,0.000559077,0.0002116743,0.0005209081,0.000501477,0.0002574092],"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":[0.00003441144,0.00001530924,0.0004714666,0.0005549754,0.00001613907,0.00001610984,0.00002271228,0.0001452026,0.0001198587,0.0003578642,0.9967695,0.001476417],"study_design_scores_gemma":[0.00009334822,0.00001179495,0.002147098,0.0001858554,0.00001670389,0.00004374592,0.00007289058,0.0001984223,0.0002020832,0.0008319933,0.9961766,0.00001950299],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005944013,0.00003255529,0.000045762,0.00003529017,0.00001334986,0.000005958449,0.9988509,0.0003452243,0.000611557],"genre_scores_gemma":[0.0001707145,0.00003423099,0.0002027451,0.00004433657,0.000003557126,0.00004381978,0.9989401,0.0001076333,0.0004528285],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8843292,"threshold_uncertainty_score":0.3869575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02030474204530373,"score_gpt":0.2631097870850578,"score_spread":0.2428050450397541,"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."}}