{"id":"W6950574402","doi":"10.5281/zenodo.8329701","title":"FutureOfAIviaAI code","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alpha Technologies (Canada); University of Toronto","funders":"","keywords":"Benchmark (surveying); Code (set theory); Big data; Competition (biology); Exponential growth; Key (lock)","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":[0.001820517,0.002040899,0.001117645,0.002303519,0.001354126,0.006058731,0.004260607,0.002938097,0.6028079],"category_scores_gemma":[0.008876715,0.001325295,0.001545719,0.00255017,0.0008958738,0.006668252,0.005513712,0.003516021,0.551446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001746104,"about_ca_system_score_gemma":0.002422025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005685077,"about_ca_topic_score_gemma":0.005977726,"domain_scores_codex":[0.998648,0.0001534137,0.0000627215,0.0002338093,0.0007095761,0.0001925726],"domain_scores_gemma":[0.9964136,0.000596483,0.000145608,0.001148765,0.00121298,0.0004825452],"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":[0.0001079512,0.00002530397,0.0001406256,0.0002473143,0.000009965263,0.00004308244,0.00003152745,0.0006666719,0.0006807061,0.008019499,0.9418907,0.04813657],"study_design_scores_gemma":[0.00004641812,0.00002073806,0.0001444488,0.00007533975,0.000005188794,0.00007718214,0.00001091543,0.003593283,0.0009210422,0.008571628,0.9865105,0.00002330967],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001158851,0.001893863,0.06588032,0.005115014,0.004129154,0.0004633694,0.1035196,0.3514466,0.4663934],"genre_scores_gemma":[0.01671596,0.002688272,0.08683649,0.003199355,0.001352037,0.001290464,0.279752,0.1706126,0.4375528],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6028079,"threshold_uncertainty_score":0.5665463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.040263184740388,"score_gpt":0.2616805077030653,"score_spread":0.2214173229626773,"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."}}