{"id":"W7154032350","doi":"10.1145/3772318.3808882","title":"10.1145/3772318.3808882","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Component (thermodynamics); Session key; Training (meteorology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001969403,0.003781096,0.002640166,0.002967075,0.002199656,0.004701566,0.003015186,0.005224441,0.9522473],"category_scores_gemma":[0.002810787,0.002026548,0.001599365,0.008696273,0.00171378,0.009029496,0.005634017,0.002862745,0.9678158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002317028,"about_ca_system_score_gemma":0.001126323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01770447,"about_ca_topic_score_gemma":0.01364557,"domain_scores_codex":[0.9992952,0.00003941408,0.00005699298,0.000210043,0.0002393134,0.0001590639],"domain_scores_gemma":[0.9984499,0.0003096886,0.00007158623,0.0005337962,0.0003518074,0.0002831558],"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":[0.0002945687,0.0002265947,0.00051368,0.0005528533,0.00005049526,0.0002385971,0.00007131181,0.0009178238,0.001718284,0.006286254,0.6586453,0.3304844],"study_design_scores_gemma":[0.00004993457,0.00004301391,0.0008904627,0.0002693435,0.00004844073,0.0001559086,0.00006977734,0.001348432,0.0007599908,0.001879841,0.9944457,0.00003912568],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002156339,0.004995187,0.01390596,0.001377285,0.002505656,0.0004608378,0.01808578,0.0207803,0.9357326],"genre_scores_gemma":[0.003689119,0.002169996,0.002375628,0.0006770581,0.0001522323,0.0002019443,0.008316215,0.002143776,0.980274],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04775274,"threshold_uncertainty_score":0.06811339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004514505607462606,"score_gpt":0.1946087019744466,"score_spread":0.190094196366984,"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."}}