{"id":"W6924774247","doi":"10.15468/dl.tvc68m","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Characterization and Applications of Magnetic Nanoparticles","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); R package","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":[0.0009887293,0.002305563,0.001639349,0.004898979,0.001069966,0.002525211,0.003042161,0.002433375,0.08925067],"category_scores_gemma":[0.004931909,0.0007994834,0.001370659,0.008739273,0.0004998182,0.001978267,0.002370039,0.002133372,0.1514562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001885966,"about_ca_system_score_gemma":0.002316859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02904628,"about_ca_topic_score_gemma":0.04617869,"domain_scores_codex":[0.9990564,0.0001302662,0.0001199428,0.0003224667,0.0002164524,0.0001545324],"domain_scores_gemma":[0.9981461,0.0005126275,0.0001830487,0.0004745521,0.0004743047,0.0002094454],"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":[0.00004316626,0.00001841177,0.0006111317,0.0007049501,0.00002282053,0.00002385846,0.00003199088,0.0002546303,0.0001927914,0.0004534648,0.9954983,0.002144378],"study_design_scores_gemma":[0.00008459564,0.00001083369,0.002325404,0.0002288784,0.00001807126,0.00004819034,0.000092792,0.0003240477,0.00029272,0.0009508142,0.9956005,0.00002323726],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006135509,0.00003846907,0.00005556472,0.00004031085,0.00001322303,0.000006718879,0.998683,0.0005176199,0.0005836796],"genre_scores_gemma":[0.0001786847,0.00003826267,0.0002637457,0.00004436909,0.000002919006,0.00004177821,0.9989381,0.0001171038,0.0003749516],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9107493,"threshold_uncertainty_score":0.2985733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01164160288666675,"score_gpt":0.19964008762195,"score_spread":0.1879984847352832,"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."}}