{"id":"W6902870987","doi":"10.7910/dvn/fmk6sq/hrxfnw","title":"103.tif","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":[0.001707723,0.004862777,0.002351477,0.007701235,0.001294899,0.005882181,0.00394814,0.004034102,0.4037816],"category_scores_gemma":[0.01223757,0.001200666,0.00262632,0.01020323,0.000901643,0.003054965,0.003401794,0.00286763,0.4675446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002162188,"about_ca_system_score_gemma":0.003692465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04049466,"about_ca_topic_score_gemma":0.06333276,"domain_scores_codex":[0.9985901,0.0002560765,0.0001442848,0.0003836465,0.000301206,0.0003247549],"domain_scores_gemma":[0.9959707,0.001198864,0.0002822028,0.001001389,0.0009976727,0.0005491709],"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":[0.00002397653,0.000009068195,0.0001381856,0.00037948,0.00001525776,0.000005690567,0.00001061875,0.00008422405,0.00002994516,0.0001755686,0.9984177,0.0007103607],"study_design_scores_gemma":[0.0004733515,0.00003163319,0.001671536,0.0006928699,0.0000386543,0.00003675206,0.0001140999,0.0003778744,0.0002260004,0.00198959,0.9942952,0.00005252049],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002527815,0.00004700585,0.00002141455,0.00008556406,0.00005213991,0.000005490362,0.9988154,0.0003647472,0.0005829631],"genre_scores_gemma":[0.0001856932,0.00007294262,0.0001319943,0.0001115615,0.00001781639,0.0000458325,0.9981074,0.0002076155,0.001119166],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5962184,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02481105642139298,"score_gpt":0.2545809091915118,"score_spread":0.2297698527701189,"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."}}