{"id":"W4393586178","doi":"10.5281/zenodo.3660456","title":"Resistance web archive collection derivatives","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Resistance (ecology); World Wide Web; Computer science; Information retrieval; Biology; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004649528,0.0002467618,0.0002899263,0.00043882,0.002363515,0.001936878,0.003762491,0.000103373,0.001887948],"category_scores_gemma":[0.001067503,0.0002648609,0.00009846362,0.001629415,0.0001540171,0.0004013968,0.003092289,0.0005540991,0.01313155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001302475,"about_ca_system_score_gemma":0.00001929679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002004398,"about_ca_topic_score_gemma":0.000004134289,"domain_scores_codex":[0.9972535,0.0006231385,0.0003268496,0.0008811477,0.0005486161,0.0003667811],"domain_scores_gemma":[0.9980026,0.00005892539,0.000258767,0.001109109,0.0003473277,0.0002231971],"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":[0.00001884668,0.00005314118,5.335776e-8,0.00007876924,0.00007586081,0.00002964796,0.0002702275,0.000006501875,0.0001749955,0.0006308529,0.9952654,0.003395672],"study_design_scores_gemma":[0.000215141,0.0001207822,0.00001400527,0.00006791817,0.00002791053,0.00002598358,0.00005851898,0.0008170033,0.00003906579,0.0001721344,0.9981681,0.0002734715],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000533386,0.00006680623,0.03324835,0.001403182,0.0001391596,0.0002275283,0.955002,0.0007975071,0.009110205],"genre_scores_gemma":[0.0001740721,0.0003558665,0.002722436,0.0002541701,0.000204517,6.516959e-8,0.9951056,0.0004645859,0.000718739],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04010362,"threshold_uncertainty_score":0.9999803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02902973352188675,"score_gpt":0.2366768129421977,"score_spread":0.2076470794203109,"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."}}