{"id":"W7009439351","doi":"","title":"Episode 4: Written employment agreements - benefits and pitfalls to avoid","year":2020,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Educational Methods and Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Labour law; Legislation; Employment contract; Job loss; Employment discrimination; Common law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0200405,0.0003759418,0.0004479265,0.0009724684,0.01423912,0.01145246,0.002596182,0.008598841,0.07874852],"category_scores_gemma":[0.08558699,0.0007003192,0.0005639096,0.001580312,0.002844995,0.006466234,0.008298561,0.0118405,0.02361021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01245568,"about_ca_system_score_gemma":0.03002854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.198688,"about_ca_topic_score_gemma":0.3424433,"domain_scores_codex":[0.9538169,0.009100194,0.002439028,0.0011436,0.027239,0.006261227],"domain_scores_gemma":[0.9585014,0.01270745,0.002280619,0.003748236,0.01721896,0.00554325],"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":[0.00002432185,0.000047542,0.0007243496,0.00008356098,0.000002361475,0.0002853772,0.005138792,0.0000493371,0.0001778609,0.03799096,0.9301726,0.02530303],"study_design_scores_gemma":[0.000007627257,0.00001213718,0.001417497,0.0002487097,0.00000245044,0.0001441536,0.009363864,0.00008039185,0.0002816762,0.003342377,0.9850748,0.00002436183],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01658538,0.001530739,0.008628406,0.2463859,0.01064866,0.001173928,0.002322861,0.001599039,0.7111251],"genre_scores_gemma":[0.08123068,0.0009045906,0.006296704,0.09053618,0.001080918,0.0007720914,0.001338716,0.000947334,0.8168927],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.198688,"threshold_uncertainty_score":0.3950631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881291356677533,"score_gpt":0.2606187904980928,"score_spread":0.2418058769313175,"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."}}