{"id":"W4394077356","doi":"10.6084/m9.figshare.14500245","title":"Data from: Is it possible to understand a book missing a quarter of the letters? Unveiling the belowground species richness of grasslands","year":2021,"lang":"en","type":"dataset","venue":"Figshare","topic":"Plant Ecology and Taxonomy Studies","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Species richness; Geography; Reference data; Database; Computer science; Library science; Archaeology; Ecology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008713525,0.000198897,0.0003615919,0.00001197543,0.0003479713,0.00006927375,0.001368692,0.0001539561,0.05899601],"category_scores_gemma":[0.0002980056,0.00006158381,0.0001078132,0.0002637086,0.00006072852,0.00009078118,0.000971759,0.0002283319,0.00008128041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000216289,"about_ca_system_score_gemma":0.0000390124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001484659,"about_ca_topic_score_gemma":0.005765589,"domain_scores_codex":[0.9988256,0.00009897855,0.0002752211,0.0003714969,0.0002150752,0.0002136329],"domain_scores_gemma":[0.9983417,0.0009167795,0.0002857587,0.0003595257,0.00006209619,0.00003408585],"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":[0.000009956491,0.00002717492,0.00008972108,0.00005985626,0.0001041268,0.000005305851,0.00009619154,3.988121e-7,0.0003131512,1.845349e-7,0.9992535,0.00004044295],"study_design_scores_gemma":[0.00005710113,0.00002822711,0.006079346,0.001085884,0.00006080467,0.000002717105,0.001518792,0.000002595777,0.0003048487,0.00001137224,0.9907011,0.000147199],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0020567,0.00105528,1.155602e-7,0.006339006,0.0001074617,0.000211542,0.9900423,0.00000486031,0.0001826797],"genre_scores_gemma":[0.001428962,0.00004652472,0.000005024791,0.002295824,0.0002199062,0.00001535031,0.9957668,7.840786e-7,0.0002208322],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05891473,"threshold_uncertainty_score":0.9418642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1527074856685605,"score_gpt":0.2661566566043079,"score_spread":0.1134491709357474,"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."}}